Physical Review Research (Aug 2022)

Leveraging randomized compiling for the quantum imaginary-time-evolution algorithm

  • Jean-Loup Ville,
  • Alexis Morvan,
  • Akel Hashim,
  • Ravi K. Naik,
  • Marie Lu,
  • Bradley Mitchell,
  • John-Mark Kreikebaum,
  • Kevin P. O'Brien,
  • Joel J. Wallman,
  • Ian Hincks,
  • Joseph Emerson,
  • Ethan Smith,
  • Ed Younis,
  • Costin Iancu,
  • David I. Santiago,
  • Irfan Siddiqi

DOI
https://doi.org/10.1103/PhysRevResearch.4.033140
Journal volume & issue
Vol. 4, no. 3
p. 033140

Abstract

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Recent progress in noisy intermediate-scale quantum (NISQ) hardware shows that quantum devices may be able to tackle complex problems even without error correction. However, coherent errors due to the increased complexity of these devices is an outstanding issue. They can accumulate through a circuit, making their impact on algorithms hard to predict and mitigate. Iterative algorithms like quantum imaginary time evolution are susceptible to these errors. This article presents the combination of both noise tailoring using randomized compiling and error mitigation with purification. We also show that cycle benchmarking gives an estimate of the reliability of the purification. We apply this method to the quantum imaginary time evolution of a transverse field Ising model and report an energy estimation error and a ground-state infidelity both below 1%. Our methodology is general and can be used for other algorithms and platforms. We show how combining noise tailoring and error mitigation will push forward the performance of NISQ devices.