How Quantum Computing Can Help with (Continuous) Optimization

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


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 \(\sqrt{T}\cdot \ln (T)\).



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.


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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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