Sample-Efficient Adaptive Calibration of Quantum Networks Using Bayesian Optimization

Cristian L. Cortes, Pascal Lefebvre, Nikolai Lauk, Michael J. Davis, Neil Sinclair, Stephen K. Gray, and Daniel Oblak
Phys. Rev. Applied 17, 034067 – Published 28 March 2022

Abstract

All physical systems employed for quantum information tasks must act as unbiased carriers of encoded quantum states. Ensuring such indistinguishability of information carriers is a major challenge in many quantum information applications, including advanced quantum communication protocols. For photons, the workhorses of quantum communication networks, it is difficult to obtain and maintain their indistinguishability because of environment-induced transformations and loss imparted by communication channels, especially in noisy scenarios. Conventional strategies to mitigate these transformations often require hardware or software overhead that is restrictive (e.g., adding noise), infeasible (e.g., on a satellite), or time-consuming for deployed networks. Here we propose and develop resource-efficient Bayesian optimization techniques to rapidly and adaptively calibrate the indistinguishability of individual photons for quantum networks using only information derived from their measurement. To experimentally validate our approach, we demonstrate the optimization of Hong-Ou-Mandel interference between two photons–a central task in quantum networking– finding rapid, efficient, and reliable convergence towards maximal photon indistinguishability in the presence of high loss and shot noise. We expect our resource-optimized and experimentally friendly methodology will allow fast and reliable calibration of indistinguishable quanta, a necessary task in distributed quantum computing, communications, and sensing, as well as for fundamental investigations.

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  • Received 24 June 2021
  • Revised 3 November 2021
  • Accepted 25 February 2022

DOI:https://doi.org/10.1103/PhysRevApplied.17.034067

© 2022 American Physical Society

Physics Subject Headings (PhySH)

Quantum Information, Science & TechnologyAtomic, Molecular & Optical

Authors & Affiliations

Cristian L. Cortes1,*, Pascal Lefebvre2, Nikolai Lauk3, Michael J. Davis4, Neil Sinclair3,5, Stephen K. Gray1,†, and Daniel Oblak2,‡

  • 1Center for Nanoscale Materials, Argonne National Laboratory, Lemont, Illinois 60439, USA
  • 2Institute for Quantum Science and Technology, and Department of Physics and Astronomy University of Calgary, 2500 University Drive NW, Calgary, Alberta T2N 1N4, Canada
  • 3Division of Physics, Mathematics and Astronomy, and Alliance for Quantum Technologies (AQT), California Institute of Technology, 1200 E. California Boulevard, Pasadena, California 91125, USA
  • 4Chemical Sciences and Engineering Division, Argonne National Laboratory, Lemont, Illinois 60439, USA
  • 5John A. Paulson School of Engineering and Applied Sciences, Harvard University, 29 Oxford Street, Cambridge, Massachusetts 02138, USA

  • *cris.cortes@qcware.com
  • gray@anl.gov
  • doblak@ucalgary.ca

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Vol. 17, Iss. 3 — March 2022

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