Variational Quantum Optimization of Nonlocality in Noisy Quantum Networks

Brian Doolittle, R. Thomas Bromley, Nathan Killoran, Eric Chitambar

Research output: Contribution to journalArticlepeer-review

Abstract

The noise and complexity inherent to quantum communication networks leads to technical challenges in designing quantum network protocols using classical methods. We address this issue with a hybrid variational quantum optimization (VQO) framework that simulates quantum networks on quantum hardware and optimizes the simulation using differential programming. We maximize nonlocality in noisy quantum networks to showcase our VQO framework. Using a classical simulator, we investigate the noise robustness of quantum nonlocality. Our VQO methods reproduce known results and uncover novel phenomena. We find that maximally entangled states maximize nonlocality in the presence of unital qubit channels, while nonmaximally entangled states can maximize nonlocality in the presence of nonunital qubit channels. Thus, we show VQO to be a practical design tool for quantum networks even when run on a classical simulator. Finally, using IBM quantum computers, we demonstrate that our VQO framework can maximize nonlocality on noisy quantum hardware. In the long term, our VQO techniques show promise of scaling beyond classical approaches and can be deployed on quantum network hardware to optimize network protocols against their inherent noise.

Original languageEnglish (US)
Article number4100127
JournalIEEE Transactions on Quantum Engineering
Volume4
DOIs
StatePublished - 2023

Keywords

  • Design and simulation tools
  • noisy intermediate-scale quantum (NISQ) algorithms and devices
  • quantum networking

ASJC Scopus subject areas

  • Software
  • Computer Science (miscellaneous)
  • Condensed Matter Physics
  • Engineering (miscellaneous)
  • Mechanical Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

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