Noise-resilient variational hybrid quantum-classical optimization

Laura Gentini, Alessandro Cuccoli, Stefano Pirandola, Paola Verrucchi, and Leonardo Banchi
Phys. Rev. A 102, 052414 – Published 16 November 2020

Abstract

Variational hybrid quantum-classical optimization is one of the most promising avenues to show the advantages of noisy intermediate-scale quantum computers in solving hard problems, such as finding the minimum-energy state of a Hamiltonian or solving some machine-learning tasks. In these devices, noise is unavoidable and impossible to error correct, yet its role in the optimization process is not well understood, especially from the theoretical viewpoint. Here we consider a minimization problem with respect to a variational state, iteratively obtained via a parametric quantum circuit, taking into account both the role of noise and the stochastic nature of quantum measurement outcomes. We show that the accuracy of the result obtained for a fixed number of iterations is bounded by a quantity related to the quantum Fisher information of the variational state. Using this bound, we study the convergence property of the quantum approximate optimization algorithm under realistic noise models, showing the robustness of the algorithm against different noise strengths.

  • Figure
  • Figure
  • Figure
  • Figure
  • Received 8 January 2020
  • Accepted 12 October 2020

DOI:https://doi.org/10.1103/PhysRevA.102.052414

©2020 American Physical Society

Physics Subject Headings (PhySH)

Quantum Information, Science & TechnologyCondensed Matter, Materials & Applied PhysicsAtomic, Molecular & Optical

Authors & Affiliations

Laura Gentini1,2, Alessandro Cuccoli1,2, Stefano Pirandola3, Paola Verrucchi4,1,2, and Leonardo Banchi1,2

  • 1Dipartimento di Fisica e Astronomia, Università di Firenze, I-50019, Sesto Fiorentino (FI), Italy
  • 2INFN, Sezione di Firenze, I-50019, Sesto Fiorentino (FI), Italy
  • 3Computer Science and York Centre for Quantum Technologies, University of York, York YO10 5GH, United Kingdom
  • 4ISC-CNR, UOS Dipartimento di Fisica, Università di Firenze, I-50019, Sesto Fiorentino (FI), Italy

Article Text (Subscription Required)

Click to Expand

References (Subscription Required)

Click to Expand
Issue

Vol. 102, Iss. 5 — November 2020

Reuse & Permissions
Access Options
Author publication services for translation and copyediting assistance advertisement

Authorization Required


×
×

Images

×

Sign up to receive regular email alerts from Physical Review A

Log In

Cancel
×

Search


Article Lookup

Paste a citation or DOI

Enter a citation
×