Variational quantum algorithm based on the minimum potential energy for solving the Poisson equation

Yuki Sato, Ruho Kondo, Satoshi Koide, Hideki Takamatsu, and Nobuyuki Imoto
Phys. Rev. A 104, 052409 – Published 10 November 2021

Abstract

Computer-aided engineering techniques are indispensable in modern engineering developments. In particular, partial differential equations are commonly used to simulate the dynamics of physical phenomena, but very large systems are often intractable within a reasonable computation time, even when using supercomputers. To overcome the inherent limit of classical computing, we present a variational quantum algorithm for solving the Poisson equation that can be implemented in noisy intermediate-scale quantum devices. The proposed method defines the total potential energy of the Poisson equation as an expectation of certain observables, which are decomposed into a linear combination of Pauli operators and simple observables. The expectation value of these observables is then minimized with respect to a parameterized quantum state. Because the number of decomposed terms is independent of the size of the problem, this method requires relatively few quantum measurements. Numerical experiments demonstrate the faster computing speed of this method compared with classical computing methods and a previous variational quantum approach. We believe that our approach brings quantum computer-aided techniques closer to future applications in engineering developments.

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  • Received 18 June 2021
  • Revised 27 September 2021
  • Accepted 22 October 2021

DOI:https://doi.org/10.1103/PhysRevA.104.052409

©2021 American Physical Society

Physics Subject Headings (PhySH)

Quantum Information, Science & TechnologyGeneral Physics

Authors & Affiliations

Yuki Sato1,*, Ruho Kondo2, Satoshi Koide1, Hideki Takamatsu3, and Nobuyuki Imoto4

  • 1Toyota Central R&D Labs., Inc., Koraku Mori Building 10F, 1-4-14 Koraku, Bunkyo-ku, Tokyo 112-0004, Japan
  • 2Toyota Central R&D Labs., Inc., 41-1 Yokomichi, Nagakute, Aichi 480-1192, Japan
  • 3Toyota Motor Corporation, 1 Toyota-Cho, Toyota, Aichi 471-8571, Japan
  • 4Institute for Photon Science and Technology, School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan

  • *yuki-sato@mosk.tytlabs.co.jp

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Issue

Vol. 104, Iss. 5 — November 2021

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