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  • Letter
  • Open Access

Efficient quantum algorithm for solving structured problems via multistep quantum computation

Hefeng Wang1,2,*, Sixia Yu3,†, and Hua Xiang4,‡

  • 1MOE Key Laboratory for Nonequilibrium Synthesis and Modulation of Condensed Matter, Xi'an Jiaotong University, Xi'an 710049, China
  • 2School of Physics, Xi'an Jiaotong University and Shaanxi Province Key Laboratory of Quantum Information and Quantum Optoelectronic Devices, Xi'an 710049, China
  • 3Hefei National Laboratory for Physical Sciences at Microscale and Department of Modern Physics, University of Science and Technology of China, Hefei, Anhui 230026, China
  • 4School of Mathematics and Statistics, Wuhan University and Hubei Key Laboratory of Computational Science, Wuhan 430072, China

  • *wanghf@mail.xjtu.edu.cn
  • †yusixia@ustc.edu.cn
  • ‡hxiang@whu.edu.cn

Phys. Rev. Research 5, L012004 – Published 17 January, 2023

DOI: https://doi.org/10.1103/PhysRevResearch.5.L012004

Abstract

In classical computation, a problem can be solved in multiple steps where the calculated results of each step can be copied and used repeatedly. However, in quantum computation, it is difficult to realize a similar multistep computation process because the no-cloning theorem forbids making copies of an unknown quantum state perfectly. We find a method based on a quantum resonant transition to protect and reuse an unknown quantum state that encodes the calculated results of an intermediate step without copying it, and present a quantum algorithm that solves a problem via multistep quantum computation. We demonstrate that this algorithm can solve a type of structured search problems efficiently.

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References (22)

  1. A. Y. Kitaev, Quantum measurements and the Abelian stabilizer problem, arXiv:quant-ph/9511026.
  2. D. S. Abrams and S. Lloyd, Quantum Algorithm Providing Exponential Speed Increase for Finding Eigenvalues and Eigenvectors, Phys. Rev. Lett. 83, 5162 (1999).
  3. D. Poulin and P. Wocjan, Preparing Ground States of Quantum Many-Body Systems on a Quantum Computer, Phys. Rev. Lett. 102, 130503 (2009).
  4. E. Farhi, J. Goldstone, and S. Gutmann, A numerical study of the performance of a quantum adiabatic evolution algorithm for satisfiability, arXiv:quant-ph/0007071.
  5. A. M. Childs, E. Deotto, E. Farhi, J. Goldstone, S. Gutmann, and A. J. Landahl, Quantum search by measurement, Phys. Rev. A 66, 032314 (2002).
  6. D. Poulin, A. Y. Kitaev, D. S. Steiger, M. B. Hastings, and M. Troyer, Quantum Algorithm for Spectral Measurement with a Lower Gate Count, Phys. Rev. Lett. 121, 010501 (2018).
  7. N. J. Cerf, L. K. Grover, and C. P. Williams, Nested quantum search and structured problems, Phys. Rev. A 61, 032303 (2000).
  8. J. Roland and N. J. Cerf, Adiabatic quantum search algorithm for structured problems, Phys. Rev. A 68, 062312 (2003).
  9. W. K. Wootters and W. H. Zurek, A single quantum cannot be cloned, Nature (London) 299, 802 (1982).
  10. D. Dieks, Communication by EPR devices, Phys. Lett. A 92, 271 (1982).
  11. H. Wang, Quantum algorithm for obtaining the eigenstates of a physical system, Phys. Rev. A 93, 052334 (2016).
  12. Z. Li, X. Liu, H. Wang, S. Ashhab, J. Cui, H. Chen, X. Peng, and J. Du, Quantum Simulation of Resonant Transitions for Solving the Eigenproblem of an Effective Water Hamiltonian, Phys. Rev. Lett. 122, 090504 (2019).
  13. D. Aharanov and A. Ta-Shma, Adiabatic quantum state generation and statistical zero knowledge, arXiv:quant-ph/0301023; Adiabatic quantum state generation, SIAM J. Comput. 37, 47 (2007).
  14. See Supplemental Material at http://link.aps.org/supplemental/10.1103/PhysRevResearch.5.L012004 for The information of error analysis of the algorithm, application of the algorithm for solving the Deutsch-Jozsa problem and the unstructured search problem, application of Grover's algorithm and the quantum adiabatic algorithm for solving the search problem with a special structure, and a summary of the performance of different algorithms for solving the search problem with a special structure.
  15. G. H. Low and I. L. Chuang, Optimal Hamiltonian Simulation by Quantum Signal Processing, Phys. Rev. Lett. 118, 010501 (2017).
  16. G. H. Low and I. L. Chuang, Hamiltonian simulation by qubitization, Quantum 3, 163 (2019).
  17. T. Monz, D. Nigg, E. A. Martinez, M. F. Brandl, P. Schindler, R. Rines, S. X. Wang, I. L. Chuang, and R. Blatt, Realization of a scalable Shor algorithm, Science 351, 1068 (2016).
  18. H. Wang, Quantum algorithm for solving the hidden subgroup problems, arXiv:2204.03295.
  19. L. K. Grover, Quantum Mechanics Helps in Searching for a Needle in a Haystack, Phys. Rev. Lett. 79, 325 (1997).
  20. J. Roland and N. J. Cerf, Quantum search by local adiabatic evolution, Phys. Rev. A 65, 042308 (2002).
  21. T. Albash and D. A. Lidar, Adiabatic quantum computation, Rev. Mod. Phys. 90, 015002 (2018).
  22. M. B. Hastings, The power of adiabatic quantum computation with no sign problem, Quantum 5, 597 (2021), and references therein.

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