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How Quantum Computing Can Help with (Continuous) Optimization

  • Christian Ayub
  • Martine Ceberio
  • Vladik KreinovichEmail author
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Part of the Studies in Systems, Decision and Control book series (SSDC, volume 276)

Abstract

It is known that the use of quantum computing can reduce the time needed for a search in an unsorted array: from the original non-quantum time T to a much smaller quantum computation time \(T_q\sim \sqrt{T}\). In this paper, we show that for a continuous optimization problem, with quantum computing, we can reach almost the same speed-up: namely, we can reduce the non-quantum time T to a much shorter quantum computation time \(\sqrt{T}\cdot \ln (T)\).

Notes

Acknowledgements

This work was supported in part by the US National Science Foundation grant HRD-1242122 (Cyber-ShARE Center of Excellence).

The authors are thankful for all the participants of the NMSU/UTEP Workshop on Mathematics, Computer Science, and Computational Science (Las Cruces, New Mexico, April 6, 2019) for valuable suggestions.

References

  1. 1.
    Grover, L.K.: A fast quantum mechanical algorithm for database search. In: Proceedings of the 28th ACM Symposium on Theory of Computing, pp. 212–219 (1996)Google Scholar
  2. 2.
    Grover, L.K.: Quantum mechanics helps in searching for a needle in a haystack. Phys. Rev. Lett. 79(2), 325–328 (1997)CrossRefGoogle Scholar
  3. 3.
    Nielsen, M., Chuang, I.: Quantum Computation and Quantum Information. Cambridge University Press, Cambridge (2000)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Christian Ayub
    • 1
  • Martine Ceberio
    • 1
  • Vladik Kreinovich
    • 1
    Email author
  1. 1.Department of Computer ScienceUniversity of Texas at El PasoEl PasoUSA

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