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Quantum Annealing Sampling with a Bias Field

Tobias Grass1,2,3,*

  • 1ICFO—Institut de Ciencies Fotoniques, The Barcelona Institute of Science and Technology, Av. Carl Friedrich Gauss 3, 08860 Castelldefels (Barcelona), Spain
  • 2DIPC—Donostia International Physics Center, Paseo Manuel de Lardizábal 4, 20018 San Sebastián, Spain
  • 3Ikerbasque—Basque Foundation for Science, Maria Diaz de Haro 3, 48013 Bilbao, Spain

  • *tobias.grass@dipc.org
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Phys. Rev. Applied 18, 044036 – Published 14 October, 2022

DOI: https://doi.org/10.1103/PhysRevApplied.18.044036

Abstract

The presence of a bias field, encoding some information about a target state, can enhance the performance of quantum optimization methods. Here we investigate the effect of such a bias field on the outcome of quantum annealing sampling, with the example of the exact cover problem. The sampling is carried out on a D-Wave machine, and different bias configurations are benchmarked against the unbiased sampling procedure. It is found that the biased annealing algorithm works particularly well for larger problem sizes, where the Hamming distance between bias and target configuration becomes less important. This work motivates future research efforts for finding good bias configurations, either on the quantum machine itself or in a hybrid fashion via classical algorithms.

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Outline

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Phys. Rev. Applied 18, 044036– Published 14 October, 2022
  • Received 31 May 2022
  • Revised 30 July 2022
  • Accepted 13 September 2022
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