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The hardness of random quantum circuits

Abstract

As Moore’s law reaches its limits, quantum computers are emerging that hold promise to dramatically outperform classical computers. It is now possible to build quantum processors with over 100 qubits, which are expected to be beyond the reach of classical simulation. These developments have been accompanied by the anticipation that, at some stage, a quantum computer should be able to perform a task that is practically impossible for any classical computer. The lead candidate for reaching this threshold is random circuit sampling, which involves sampling the output of a quantum computer after implementing a sequence of random quantum operations. However, it is difficult to provide theoretical guarantees on the hardness of simulating random quantum circuits by classical computers. Here we prove that estimating the output probabilities of random quantum circuits is #P-hard for any classical computer. We also extend our results to a restricted model of quantum computation known as instantaneous quantum polynomial-time (IQP) circuits. We achieve this by a worst-case to average-case reduction for quantum-circuit simulation. The robustness of our result to the estimation error serves as a new hardness criterion for the performance of classical algorithms. Our results suggest that there is an exponential hardness barrier for the approximate classical simulation of most quantum circuits.

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Fig. 1: Architecture \({\mathcal{A}}\) and a quantum circuit instantiation.
Fig. 2: Cayley path interpolation in the unitary group.
Fig. 3: Overview of the average-case hardness proof.

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Code sharing is not applicable to this Article as there are no codes or algorithms beyond what appears in the paper and the Supplementary Information.

References

  1. Richard, P. Feynman. Quantum mechanical computers. Opt. News 11, 11–20 (1985).

    Article  MathSciNet  Google Scholar 

  2. Shor, P. W. Polynomial-time algorithms for prime factorization and discrete logarithms on a quantum computer. SIAM Rev. 41, 303–332 (1999).

    Article  ADS  MathSciNet  MATH  Google Scholar 

  3. Harrow, A. W., Hassidim, A. & Lloyd, S. Quantum algorithm for linear systems of equations. Phys. Rev. Lett. 103, 150502 (2009).

    Article  ADS  MathSciNet  Google Scholar 

  4. Childs, A. M. Universal computation by quantum walk. Phys. Rev. Lett. 102, 180501 (2009).

    Article  ADS  MathSciNet  Google Scholar 

  5. Preskill, J. Quantum computing in the NISQ era and beyond. Quantum 2, 79 (2018).

    Article  Google Scholar 

  6. Arute, F. et al. Quantum supremacy using a programmable superconducting processor. Nature 574, 505–510 (2019).

    Article  ADS  Google Scholar 

  7. Chow, J., Dial, O. & Gambetta, J. IBM Quantum Breaks the 100-qubit Processor Barrier (IBM, 2021); https://research.ibm.com/blog/127-qubit-quantum-processor-eagle

  8. Harrow, A. W. & Montanaro, A. Quantum computational supremacy. Nature 549, 203–209 (2017).

    Article  ADS  Google Scholar 

  9. Lund, A. P., Bremner, M. J. & Ralph, T. C. Quantum sampling problems, BosonSampling and quantum supremacy. npj Quantum Inf. 3, 15 (2017).

    Article  ADS  Google Scholar 

  10. Boixo, S. et al. Characterizing quantum supremacy in near-term devices. Nat. Phys. 14, 595–600 (2018).

    Article  Google Scholar 

  11. Mi, X. et al. Information scrambling in quantum circuits. Science 374, 1479–1483 (2021).

    Article  ADS  Google Scholar 

  12. Lavasani, A., Alavirad, Y. & Barkeshli, M. Measurement-induced topological entanglement transitions in symmetric random quantum circuits. Nat. Phys. 17, 342–347 (2021).

    Article  Google Scholar 

  13. Shtanko, O. & Movassagh, R. Algorithms for Gibbs state preparation on noiseless and noisy random quantum circuits. Preprint at arXiv https://doi.org/10.48550/arXiv.2112.14688 (2021).

  14. Chen, L. & Movassagh, R. Quantum Merkle trees. Preprint at arXiv https://doi.org/10.48550/arXiv.2112.14317 (2021).

  15. Stockmeyer, L. On approximation algorithms for #P. SIAM J. Comput. 14, 849–861 (1985).

    Article  MathSciNet  MATH  Google Scholar 

  16. Napp, J. C., La Placa, R. L., Dalzell, A. M., Brandão, F. G. S. L. & Harrow, A. W. Efficient classical simulation of random shallow 2D quantum circuits. Preprint at arXiv https://doi.org/10.48550/arXiv.2001.0002 (2020).

  17. Gray, J. & Kourtis, S. Hyper-optimized tensor network contraction. Quantum 5, 410 (2021).

    Article  Google Scholar 

  18. Huang, C. et al. Classical simulation of quantum supremacy circuits. Preprint at arXiv https://doi.org/10.48550/arXiv.2005.06787 (2020).

  19. Pan, F., Chen, K. & Zhang, P. Solving the sampling problem of the sycamore quantum circuits. Phys. Rev. Lett. 129, 090502 (2022).

    Article  ADS  Google Scholar 

  20. Harrow, A. W. & Mehraban, S. Approximate unitary t-designs by short random quantum circuits using nearest-neighbor and long-range gates. Commun. Math. Phys. 1–96 (2023).

  21. Hangleiter, D., Bermejo-Vega, J., Schwarz, M. & Eisert, J. Anticoncentration theorems for schemes showing a quantum speedup. Quantum 2, 65 (2018).

    Article  Google Scholar 

  22. Oszmaniec, M., Dangniam, N., Morales, M. E. & Zimborás, Z. Fermion sampling: a robust quantum computational advantage scheme using fermionic linear optics and magic input states. PRX Quantum 3, 020328 (2022).

    Article  ADS  Google Scholar 

  23. Kondo, Y., Mori, R. & Movassagh, R. Quantum supremacy and hardness of estimating output probabilities of quantum circuits. In 2021 IEEE 62nd Annual Symposium on Foundations of Computer Science (FOCS) 1296–1307 (IEEE, 2022).

  24. Bouland, A., Fefferman, B., Landau, Z. & Liu, Y. Noise and the frontier of quantum supremacy. In 2021 IEEE 62nd Annual Symposium on Foundations of Computer Science (FOCS) 1308–1317 (IEEE, 2022).

  25. Bravyi, S., Gosset, D. & Movassagh, R. Classical algorithms for quantum mean values. Nat. Phys. 17, 337–341 (2021).

    Article  Google Scholar 

  26. Hayden, P. & Preskill, J. Black holes as mirrors: quantum information in random subsystems. J. High Energy Phys. 2007, 120 (2007).

    Article  MathSciNet  Google Scholar 

  27. Takayanagi, T. Holographic spacetimes as quantum circuits of path-integrations. J. High Energy Phys. https://doi.org/10.1007/JHEP12(2018)048 (2018).

  28. Welch, L. R. & Berlekamp, E. R. Error correction for algebraic block codes. US patent 4,633,470 (1986).

  29. Reed, I. S. & Solomon, G. Polynomial codes over certain finite fields. J. Soc. Industrial Appl. Math. 8, 300–304 (1960).

    Article  MathSciNet  MATH  Google Scholar 

  30. Aaronson, S. & Arkhipov, A. The computational complexity of linear optics. In Proc. Forty-Third Annual ACM Symposium on Theory of Computing 333–342 (ACM, 2011).

  31. Bremner, M. J., Jozsa, R. & Shepherd, D. J. Classical simulation of commuting quantum computations implies collapse of the polynomial hierarchy. Proc. R. Soc. A 467, 459–472 (2011).

    Article  ADS  MathSciNet  MATH  Google Scholar 

  32. Bremner, M. J., Montanaro, A. & Shepherd, D. J. Achieving quantum supremacy with sparse and noisy commuting quantum computations. Quantum 1, 8 (2017).

    Article  Google Scholar 

  33. Bouland, A., Fefferman, B., Nirkhe, C. & Vazirani, U. On the complexity and verification of quantum random circuit sampling. Nat. Phys. 15, 159–163 (2019).

    Article  MATH  Google Scholar 

  34. Wu, Y. et al. Strong quantum computational advantage using a superconducting quantum processor. Phys. Rev. Lett. 127, 180501 (2021).

    Article  ADS  Google Scholar 

  35. Zhu, Q. et al. Quantum computational advantage via 60-qubit 24-cycle random circuit sampling. Sci. Bull. 67, 240–245 (2022).

    Article  Google Scholar 

  36. Dalzell, A. M., Hunter-Jones, N. & Brandao, F. G. S. L. Random quantum circuits anticoncentrate in log depth. PRX Quantum 3, 010333 (2022).

    Article  ADS  Google Scholar 

  37. Terhal, B. M. & DiVincenzo, D. P. Adaptive quantum computation, constant depth quantum circuits and Arthur-Merlin games. Quant. Inf. Comp. 4, 134–145 (2004).

    MathSciNet  MATH  Google Scholar 

  38. Aaronson, S. & Arkhipov, A. The computational complexity of linear optics. Preprint at arXiv https://doi.org/10.48550/arXiv.1011.3245 (2011).

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Acknowledgements

I thank R. Mori and S. Bravyi for discussions. I also thank S. Boixo, Y. Kondo, O. Shtanko, J. Schenker, A. Bouland, B. Fefferman, Y. Liu, L. Chen, J. Napp, A. Dalzell and K. Zyczkowski. This work was partly supported by the Frontiers Foundation and the MIT-IBM collaborative grant.

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R. Movassagh is the sole author of this work.

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Correspondence to Ramis Movassagh.

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Movassagh, R. The hardness of random quantum circuits. Nat. Phys. 19, 1719–1724 (2023). https://doi.org/10.1038/s41567-023-02131-2

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