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Logical Error Rates of XZZX and Rotated Quantum Surface Codes (2312.17057v1)

Published 28 Dec 2023 in quant-ph, cs.IT, and math.IT

Abstract: Surface codes are versatile quantum error-correcting codes known for their planar geometry, making them ideal for practical implementations. While the original proposal used Pauli $X$ or Pauli $Z$ operators in a square structure, these codes can be improved by rotating the lattice or incorporating a mix of generators in the XZZX variant. However, a comprehensive theoretical analysis of the logical error rate for these variants has been lacking. To address this gap, we present theoretical formulas based on recent advancements in understanding the weight distribution of stabilizer codes. For example, over an asymmetric channel with asymmetry $A=10$ and a physical error rate $p \to 0$, we observe that the logical error rate asymptotically approaches $p_\mathrm{L} \to 10 p2$ for the rotated $[[9,1,3]]$ XZZX code and $p_\mathrm{L} \to 18.3 p2$ for the $[[13,1,3]]$ surface code. Additionally, we observe a particular behavior regarding rectangular lattices in the presence of asymmetric channels. Our findings demonstrate that implementing both rotation and XZZX modifications simultaneously can lead to suboptimal performance. Thus, in scenarios involving a rectangular lattice, it is advisable to avoid using both modifications simultaneously. This research enhances our theoretical understanding of the logical error rates for XZZX and rotated surface codes, providing valuable insights into their performance under different conditions.

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References (33)
  1. P. W. Shor, “Scheme for reducing decoherence in quantum computer memory,” Phys. Rev. A, vol. 52, pp. R2493–R2496, Oct 1995.
  2. H. J. Kimble, “The quantum internet,” Nature, vol. 453, no. 7198, p. 1023, 2008.
  3. S. Muralidharan, L. Li, J. Kim, N. Lütkenhaus, M. D. Lukin, and L. Jiang, “Optimal architectures for long distance quantum communication,” Scientific reports, vol. 6, p. 20463, 2016.
  4. S. Wehner, D. Elkouss, and R. Hanson, “Quantum internet: A vision for the road ahead,” Science, vol. 362, no. 6412, 2018.
  5. A. S. Cacciapuoti, M. Caleffi, R. Van Meter, and L. Hanzo, “When entanglement meets classical communications: Quantum teleportation for the quantum Internet,” IEEE Trans. on Comm., vol. 68, no. 6, pp. 3808–3833, 2020.
  6. L. Valentini, R. B. Christensen, P. Popovski, and M. Chiani, “Reliable quantum communications based on asymmetry in purification and coding,” arXiv preprint arXiv:2305.00949, 2023.
  7. D. Gottesman, “An introduction to quantum error correction and fault-tolerant quantum computation,” arXiv preprint quant-ph/0904.2557, 2009.
  8. B. M. Terhal, “Quantum error correction for quantum memories,” Rev. Mod. Phys., vol. 87, pp. 307–346, Apr 2015.
  9. Z. Babar, D. Chandra, H. V. Nguyen, P. Botsinis, D. Alanis, S. X. Ng, and L. Hanzo, “Duality of quantum and classical error correction codes: Design principles and examples,” IEEE Communications Surveys Tutorials, vol. 21, no. 1, pp. 970–1010, Firstquarter 2019.
  10. M. Chiani, A. Conti, and M. Z. Win, “Piggybacking on quantum streams,” Physical Review A, vol. 102, no. 1, jul 2020.
  11. D. Ostrev, D. Orsucci, F. Lázaro, and B. Matuz, “Classical product code constructions for quantum Calderbank-Shor-Steane codes,” 2022. [Online]. Available: https://arxiv.org/abs/2209.13474
  12. F. Zoratti, G. De Palma, and V. Giovannetti, “Improving the speed of variational quantum algorithms for quantum error correction,” arXiv preprint arXiv:2301.05273, 2023.
  13. S. B. Bravyi and A. Y. Kitaev, “Quantum codes on a lattice with boundary,” 1998.
  14. A. G. Fowler, M. Mariantoni, J. M. Martinis, and A. N. Cleland, “Surface codes: Towards practical large-scale quantum computation,” Physical Review A, vol. 86, no. 3, sep 2012.
  15. C. Horsman, A. G. Fowler, S. Devitt, and R. V. Meter, “Surface code quantum computing by lattice surgery,” New Journal of Physics, vol. 14, no. 12, p. 123011, dec 2012.
  16. J. P. B. Ataides, D. K. Tuckett, S. D. Bartlett, S. T. Flammia, and B. J. Brown, “The XZZX surface code,” Nature Communications, vol. 12, no. 1, apr 2021.
  17. S. Krinner, N. Lacroix, A. Remm, A. Di Paolo, E. Genois, C. Leroux, C. Hellings, S. Lazar, F. Swiadek, J. Herrmann et al., “Realizing repeated quantum error correction in a distance-three surface code,” Nature, vol. 605, no. 7911, pp. 669–674, 2022.
  18. Y. Zhao, Y. Ye, H.-L. Huang, Y. Zhang, D. Wu, H. Guan, Q. Zhu, Z. Wei, T. He, S. Cao, F. Chen, T.-H. Chung, H. Deng, D. Fan, M. Gong, C. Guo, S. Guo, L. Han, N. Li, S. Li, Y. Li, F. Liang, J. Lin, H. Qian, H. Rong, H. Su, L. Sun, S. Wang, Y. Wu, Y. Xu, C. Ying, J. Yu, C. Zha, K. Zhang, Y.-H. Huo, C.-Y. Lu, C.-Z. Peng, X. Zhu, and J.-W. Pan, “Realization of an error-correcting surface code with superconducting qubits,” Phys. Rev. Lett., vol. 129, p. 030501, Jul 2022.
  19. Google Quantum AI, “Suppressing quantum errors by scaling a surface code logical qubit,” Nature, vol. 614, no. 7949, pp. 676–681, 2023.
  20. S. Bravyi, M. Suchara, and A. Vargo, “Efficient algorithms for maximum likelihood decoding in the surface code,” Physical Review A, vol. 90, no. 3, p. 032326, 2014.
  21. A. E. Ashikhmin, A. M. Barg, E. Knill, and S. N. Litsyn, “Quantum error detection. I. statement of the problem,” IEEE Trans. Inf. Theory, vol. 46, no. 3, pp. 778–788, 2000.
  22. ——, “Quantum error detection. II. bounds,” IEEE Trans. Inf. Theory, vol. 46, no. 3, pp. 789–800, 2000.
  23. D. Forlivesi, L. Valentini, and M. Chiani, “Performance analysis of quantum error-correcting codes via MacWilliams identities,” arXiv preprint arXiv:2305.01301, 2023.
  24. A. S. Fletcher, P. W. Shor, and M. Z. Win, “Structured near-optimal channel-adapted quantum error correction,” Phys. Rev. A, vol. 77, p. 012320, Jan 2008.
  25. P. K. Sarvepalli, A. Klappenecker, and M. Rötteler, “Asymmetric quantum codes: constructions, bounds and performance,” Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, vol. 465, no. 2105, pp. 1645–1672, 2009.
  26. M. Chiani and L. Valentini, “Short codes for quantum channels with one prevalent Pauli error type,” IEEE J. on Selected Areas in Information Theory, vol. 1, no. 2, pp. 480–486, 2020.
  27. J. ur Rehman and H. Shin, “Entanglement-free parameter estimation of generalized Pauli channels,” Quantum, vol. 5, p. 490, 2021.
  28. A. G. Fowler, A. M. Stephens, and P. Groszkowski, “High-threshold universal quantum computation on the surface code,” Physical Review A, vol. 80, no. 5, nov 2009.
  29. D. MacKay, G. Mitchison, and P. McFadden, “Sparse-graph codes for quantum error correction,” IEEE Trans. Inf. Theory, vol. 50, no. 10, pp. 2315–2330, 2004.
  30. S. Bravyi, A. W. Cross, J. M.Gambetta, D. Maslov, P. Rall, and T. J. Yoder, “High-threshold and low-overhead fault-tolerant quantum memory,” arXiv preprint arXiv:2308.07915, 2023.
  31. O. Higgott, “Pymatching: A Python package for decoding quantum codes with minimum-weight perfect matching,” ACM Transactions on Quantum Computing, vol. 3, no. 3, pp. 1–16, 2022.
  32. J. Roffe, “Quantum error correction: an introductory guide,” Contemporary Physics, vol. 60, no. 3, pp. 226–245, jul 2019.
  33. B. Dezső, A. Jüttner, and P. Kovács, “Lemon–an open source C++ graph template library,” Electronic notes in theoretical computer science, vol. 264, no. 5, pp. 23–45, 2011.
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