Optimization of Algorithmic Errors in Analog Quantum Simulations
Abstract: Analog quantum simulation is emerging as a powerful tool for uncovering classically unreachable physics such as many-body real-time dynamics. A complete quantification of uncertainties is necessary in order to make precise predictions using simulations on modern-day devices. Therefore, the inherent physical limitations of the device on the parameters of the simulation must be understood. This analysis examines the interplay of errors arising from simulation of approximate time evolution with those due to practical, real-world device constraints. These errors are studied in Heisenberg-type systems on analog quantum devices described by the Ising Hamiltonian. A general framework for quantifying these errors is introduced and applied to several proposed time evolution methods, including Trotter-like methods and Floquet-engineered constant-field approaches. The limitations placed on the accuracy of time evolution methods by current devices are discussed. Characterization of the scaling of coherent effects of different error sources provides a way to extend the presented Hamiltonian engineering methods to take advantage of forthcoming device capabilities.
- J. Preskill, Simulating quantum field theory with a quantum computer, PoS LATTICE2018, 024 (2018), arXiv:1811.10085 [hep-lat] .
- S. P. Jordan, K. S. M. Lee, and J. Preskill, Quantum algorithms for quantum field theories, Science 336, 1130 (2012).
- S. P. Jordan, K. S. M. Lee, and J. Preskill, Quantum algorithms for fermionic quantum field theories (2014a), arXiv:1404.7115 [hep-th] .
- S. P. Jordan, K. S. M. Lee, and J. Preskill, Quantum computation of scattering in scalar quantum field theories, Quantum Info. Comput. 14, 1014–1080 (2014b).
- M. Unsal, Theta dependence, sign problems and topological interference, Phys. Rev. D 86, 105012 (2012), arXiv:1201.6426 [hep-th] .
- R. P. Feynman, Simulating physics with computers, International Journal of Theoretical Physics 21, 467 (1982).
- P. Benioff, The computer as a physical system: A microscopic quantum mechanical hamiltonian model of computers as represented by turing machines, Journal of Statistical Physics 22, 563–591 (1980).
- K. Bharti et al., Noisy intermediate-scale quantum algorithms, Rev. Mod. Phys. 94, 015004 (2022), arXiv:2101.08448 [quant-ph] .
- A. Ciavarella, N. Klco, and M. J. Savage, Trailhead for quantum simulation of SU(3) Yang-Mills lattice gauge theory in the local multiplet basis, Phys. Rev. D 103, 094501 (2021), arXiv:2101.10227 [quant-ph] .
- I. M. Georgescu, S. Ashhab, and F. Nori, Quantum Simulation, Rev. Mod. Phys. 86, 153 (2014), arXiv:1308.6253 [quant-ph] .
- S. Ebadi et al., Quantum phases of matter on a 256-atom programmable quantum simulator, Nature 595, 227 (2021), arXiv:2012.12281 [quant-ph] .
- C. Monroe et al., Programmable quantum simulations of spin systems with trapped ions, Rev. Mod. Phys. 93, 025001 (2021), arXiv:1912.07845 [quant-ph] .
- S.-S. Gong, W. Zhu, and D. N. Sheng, Emergent chiral spin liquid: Fractional quantum hall effect in a kagome heisenberg model, Scientific Reports 4, 10.1038/srep06317 (2014).
- T. S. Cubitt, A. Montanaro, and S. Piddock, Universal quantum hamiltonians, Proceedings of the National Academy of Sciences 115, 9497–9502 (2018).
- C. W. Bauer et al., Quantum Simulation for High-Energy Physics, PRX Quantum 4, 027001 (2023b), arXiv:2204.03381 [quant-ph] .
- S. Caspar and H. Singh, From Asymptotic Freedom to θ𝜃\thetaitalic_θ Vacua: Qubit Embeddings of the O(3) Nonlinear σ𝜎\sigmaitalic_σ Model, Phys. Rev. Lett. 129, 022003 (2022), arXiv:2203.15766 [hep-lat] .
- J. Maldacena, A simple quantum system that describes a black hole (2023), arXiv:2303.11534 [hep-th] .
- R. Verresen, Everything is a quantum ising model (2023), arXiv:2301.11917 [quant-ph] .
- L. S. Martin et al., Controlling Local Thermalization Dynamics in a Floquet-Engineered Dipolar Ensemble, Phys. Rev. Lett. 130, 210403 (2023), arXiv:2209.09297 [quant-ph] .
- P. Scholl et al., Microwave Engineering of Programmable XXZ Hamiltonians in Arrays of Rydberg Atoms, PRX Quantum 3, 020303 (2022), arXiv:2107.14459 [quant-ph] .
- M. L. Wall, A. Safavi-Naini, and A. M. Rey, Boson-mediated quantum spin simulators in transverse fields: xy𝑥𝑦xyitalic_x italic_y model and spin-boson entanglement, Phys. Rev. A 95, 013602 (2017).
- T. G. Kiely and J. K. Freericks, Relationship between the transverse-field ising model and the xy𝑥𝑦xyitalic_x italic_y model via the rotating-wave approximation, Phys. Rev. A 97, 023611 (2018).
- A. Browaeys and T. Lahaye, Many-body physics with individually controlled rydberg atoms, Nature Physics 16, 132–142 (2020).
- G. Roumpos, C. P. Master, and Y. Yamamoto, Quantum simulation of spin ordering with nuclear spins in a solid-state lattice, Phys. Rev. B 75, 094415 (2007).
- S. Lloyd and J.-J. E. Slotine, Analog quantum error correction, Phys. Rev. Lett. 80, 4088 (1998).
- K. Fukui, A. Tomita, and A. Okamoto, Analog quantum error correction with encoding a qubit into an oscillator, Phys. Rev. Lett. 119, 180507 (2017).
- N. Klco and M. J. Savage, Digitization of scalar fields for quantum computing, Phys. Rev. A 99, 052335 (2019), arXiv:1808.10378 [quant-ph] .
- A. M. Childs and Y. Su, Nearly optimal lattice simulation by product formulas, Physical Review Letters 123, 10.1103/physrevlett.123.050503 (2019).
- S. Endo, S. C. Benjamin, and Y. Li, Practical quantum error mitigation for near-future applications, Physical Review X 8, 10.1103/physrevx.8.031027 (2018).
- R. Trivedi, A. F. Rubio, and J. I. Cirac, Quantum advantage and stability to errors in analogue quantum simulators (2022), arXiv:2212.04924 [quant-ph] .
- L. Masanes, G. Vidal, and J. I. Latorre, Time-optimal hamiltonian simulation and gate synthesis using homogeneous local unitaries (2002), arXiv:quant-ph/0202042 [quant-ph] .
- M. Suzuki, Generalized trotter’s formula and systematic approximants of exponential operators and inner derivations with applications to many-body problems, Communications in Mathematical Physics 51, 183–190 (1976).
- M. Saffman, T. G. Walker, and K. Mølmer, Quantum information with rydberg atoms, Rev. Mod. Phys. 82, 2313 (2010).
- B. Şahinoğlu and R. D. Somma, Hamiltonian simulation in the low-energy subspace, npj Quantum Information 7, 10.1038/s41534-021-00451-w (2021).
- M. Heyl, P. Hauke, and P. Zoller, Quantum localization bounds trotter errors in digital quantum simulation, Science Advances 5, eaau8342 (2019), https://www.science.org/doi/pdf/10.1126/sciadv.aau8342 .
- B. Müller and X. Yao, Simple hamiltonian for quantum simulation of strongly coupled 2+1d su(2) lattice gauge theory on a honeycomb lattice (2023), arXiv:2307.00045 [quant-ph] .
- https://iqus.uw.edu (2023).
- https://phys.washington.edu (2023a).
- https://artsci.washington.edu (2023b).
- G. Van Rossum and F. L. Drake, Python 3 Reference Manual (CreateSpace, Scotts Valley, CA, 2009).
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