Abstract
We study a classical model for the accumulation of errors in multi-qubit quantum computations. By modeling the error process in a quantum computation using two coupled Markov chains, we are able to capture a weak form of time-dependency between errors in the past and future. By subsequently using techniques from the field of discrete probability theory, we calculate the probability that error quantities such as the fidelity and trace distance exceed a threshold analytically. The formulae cover fairly generic error distributions, cover multi-qubit scenarios, and are applicable to the randomized benchmarking protocol. To combat the numerical challenge that may occur when evaluating our expressions, we additionally provide an analytical bound on the error probabilities that is of lower numerical complexity. Besides this, we study a model describing continuous errors accumulating in a single qubit. Finally, taking inspiration from the field of operations research, we illustrate how our expressions can be used to decide how many gates one can apply before too many errors accumulate with high probability, and how one can lower the rate of error accumulation in existing circuits through simulated annealing.
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References
Aaronson, S., Gottesman, D.: Improved simulation of stabilizer circuits. Phys. Rev. A 70(5), 052328 (2004)
Amy, M.: Formal methods in quantum circuit design (2019)
Ball, H., Stace, T.M., Flammia, S.T., Biercuk, M.J.: Effect of noise correlations on randomized benchmarking. Phys. Rev. A 93(2), 022303 (2016)
Bennett, C.H., Brassard, G., Crépeau, C., Jozsa, R., Peres, A., Wootters, W.K.: Teleporting an unknown quantum state via dual classical and Einstein-Podolsky-Rosen channels. Phys. Rev. Lett. 70(13), 1895 (1993)
Bennett, C.H., Wiesner, S.J.: Communication via one- and two-particle operators on Einstein-Podolsky-Rosen states. Phys. Rev. Lett. 69(20), 2881 (1992)
Bhatia, R.: Matrix Analysis, vol. 169. Springer Science & Business Media (2013). https://doi.org/10.1007/978-1-4612-0653-8
Bravyi, S., Englbrecht, M., König, R., Peard, N.: Correcting coherent errors with surface codes. npj Quantum Inf. 4(1), 55 (2018)
Brémaud, P.: Discrete Probability Models and Methods, vol. 78. Springer (2017). https://doi.org/10.1007/978-3-319-43476-6
Brown, W.G., Eastin, B.: Randomized benchmarking with restricted gate sets. Phys. Rev. A 97(6), 062323 (2018)
Carignan-Dugas, A., Boone, K., Wallman, J.J., Emerson, J.: From randomized benchmarking experiments to gate-set circuit fidelity: how to interpret randomized benchmarking decay parameters. New J. Phys. 20(9), 092001 (2018)
Cleve, R., Ekert, A., Macchiavello, C., Mosca, M.: Quantum algorithms revisited. Proc. Royal Soc. London. Ser. A: Math. Phys. Eng. Sci. 454(1969), 339–354 (1998)
Cramer, J., et al.: Repeated quantum error correction on a continuously encoded qubit by real-time feedback. Nat. Commun. 7, 11526 (2016)
Deutsch, D., Jozsa, R.: Rapid solution of problems by quantum computation. Proc. Royal Soc. London. Ser. A: Math. Phys. Sci. 439(1907), 553–558 (1992)
Epstein, J.M., Cross, A.W., Magesan, E., Gambetta, J.M.: Investigating the limits of randomized benchmarking protocols. Phys. Rev. A 89(6), 062321 (2014)
Fong, B.H., Merkel, S.T.: Randomized benchmarking, correlated noise, and ising models. arXiv preprint arXiv:1703.09747 (2017)
Fowler, A.G., Hollenberg, L.C.: Scalability of Shor’s algorithm with a limited set of rotation gates. Phys. Rev. A 70(3), 032329 (2004)
França, D.S., Hashagen, A.: Approximate randomized benchmarking for finite groups. J. Phys. A: Math. Theoret. 51(39), 395302 (2018)
Fujii, K.: Stabilizer formalism and its applications. In: Quantum Computation with Topological Codes, pp. 24–55. Springer (2015). https://doi.org/10.1007/978-981-287-996-7
Gottesman, D.: The Heisenberg representation of quantum computers. arXiv preprint quant-ph/9807006 (1998)
Gottesman, D.: Efficient fault tolerance. Nature 540, 44 (2016)
Greenbaum, D., Dutton, Z.: Modeling coherent errors in quantum error correction. Quantum Sci. Technol. 3(1), 015007 (2017)
Greenberger, D.M., Horne, M.A., Zeilinger, A.: Going beyond Bell’s theorem. In: Bell’s Theorem, Quantum Theory and Conceptions of the Universe, pp. 69–72. Springer (1989). https://doi.org/10.1007/978-94-017-0849-4_10
Gutiérrez, M., Svec, L., Vargo, A., Brown, K.R.: Approximation of realistic errors by Clifford channels and Pauli measurements. Phys. Rev. A 87(3), 030302 (2013)
Gutmann, H.: Description and control of decoherence in quantum bit systems. Ph.D. thesis, lmu (2005)
Harper, R., Hincks, I., Ferrie, C., Flammia, S.T., Wallman, J.J.: Statistical analysis of randomized benchmarking. Phys. Rev. A 99(5), 052350 (2019)
Huang, E., Doherty, A.C., Flammia, S.: Performance of quantum error correction with coherent errors. Phys. Rev. A 99(2), 022313 (2019)
Janardan, S., Tomita, Yu., Gutiérrez, M., Brown, K.R.: Analytical error analysis of Clifford gates by the fault-path tracer method. Quantum Inf. Process. 15(8), 3065–3079 (2016). https://doi.org/10.1007/s11128-016-1330-z
Kliuchnikov, V., Maslov, D.: Optimization of Clifford circuits. Phys. Rev. A 88(5), 052307 (2013)
Knill, E.: Quantum computing with realistically noisy devices. Nature 434(7029), 39 (2005)
Koenig, R., Smolin, J.A.: How to efficiently select an arbitrary Clifford group element. J. Math. Phys. 55(12), 122202 (2014)
Linke, N.M., et al.: Fault-tolerant quantum error detection. Sci. Adv. 3(10), e1701074 (2017)
Ma, L., Sanders, J.: Markov chains and hitting times for error accumulation in quantum circuits. arXiv preprint arXiv:1909.04432 (2021)
Magesan, E., Gambetta, J.M., Emerson, J.: Scalable and robust randomized benchmarking of quantum processes. Phys. Rev. Lett. 106(18), 180504 (2011)
Magesan, E., Puzzuoli, D., Granade, C.E., Cory, D.G.: Modeling quantum noise for efficient testing of fault-tolerant circuits. Phys. Rev. A 87(1), 012324 (2013)
Maslov, D., Dueck, G.W., Miller, D.M., Negrevergne, C.: Quantum circuit simplification and level compaction. IEEE Trans. Comput.-Aided Des. Integrated Circ. Syst. 27(3), 436–444 (2008)
Moll, N., et al.: Quantum optimization using variational algorithms on near-term quantum devices. Quantum Sci. Technol. 3(3), 030503 (2018)
Nielsen, M.A., Chuang, I.L.: Quantum Computation and Quantum Information: 10th Anniversary Edition, 10th edn. Cambridge University Press, New York (2011)
Preskill, J.: Quantum computing: pro and con. Proc. Royal Soc. London. Ser. A: Math. Phys. Eng. Sci. 454(1969), 469–486 (1998)
Proctor, T., Rudinger, K., Young, K., Sarovar, M., Blume-Kohout, R.: What randomized benchmarking actually measures. Phys. Rev. Lett. 119(13), 130502 (2017)
Roberts, P.H., Ursell, H.D.: Random walk on a sphere and on a Riemannian manifold. Philos. Trans. Royal Soc. London. Ser. A, Math. Phys. Sci. 252(1012), 317–356 (1960)
Ruskai, M.B.: Pauli exchange errors in quantum computation. Phys. Rev. Lett. 85(1), 194 (2000)
Selinger, P.: Generators and relations for n-qubit Clifford operators. Logical Meth. Comput. Sci. 11 (2013)
Wallman, J.J.: Randomized benchmarking with gate-dependent noise. Quantum 2, 47 (2018). https://doi.org/10.22331/q-2018-01-29-47
Wallman, J.J., Barnhill, M., Emerson, J.: Robust characterization of loss rates. Phys. Rev. Lett. 115(6), 060501 (2015)
Wood, C.J., Gambetta, J.M.: Quantification and characterization of leakage errors. Phys. Rev. A 97(3), 032306 (2018)
Xia, T., et al.: Randomized benchmarking of single-qubit gates in a 2D array of neutral-atom qubits. Phys. Rev. Lett. 114(10), 100503 (2015)
Acknowledgments
We are grateful to Bart van Schooten, who contributed the code on TU/e’s GitLab server. Finally, this research received financial support from the Chinese Scholarship Council (CSC) in the form of a CSC Scholarship.
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Ma, L., Sanders, J. (2021). Markov Chains and Hitting Times for Error Accumulation in Quantum Circuits. In: Zhao, Q., Xia, L. (eds) Performance Evaluation Methodologies and Tools. VALUETOOLS 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 404. Springer, Cham. https://doi.org/10.1007/978-3-030-92511-6_3
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