Quantum Receiver Enhanced by Adaptive Learning

Chaohan Cui, William Horrocks, Saikat Guha, N. Peyghambarian, Quntao Zhuang, Zheshen Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Adaptive quantum receiver designed by machine learning is demonstrated for discriminating multiple nonorthogonal coherent states, achieving reduced error rates of 20% (50%) over existing quantum (classical) receivers.

Original languageEnglish (US)
Title of host publicationCLEO
Subtitle of host publicationQELS_Fundamental Science, QELS 2022
PublisherOptica Publishing Group (formerly OSA)
ISBN (Electronic)9781557528209
StatePublished - 2022
EventCLEO: QELS_Fundamental Science, QELS 2022 - San Jose, United States
Duration: May 15 2022May 20 2022

Publication series

NameOptics InfoBase Conference Papers


ConferenceCLEO: QELS_Fundamental Science, QELS 2022
Country/TerritoryUnited States
CitySan Jose

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Mechanics of Materials


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