Entangled Sensor Networks Empowered by Machine Learning

Yi Xia, Wei Li, William Clar, Darlene Hart, Quntao Zhuang, Zheshen Zhang

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

Abstract

We propose and experimentally demonstrate a reconfigurable radio-frequency photonic sensor network based on continuous-variable multipartite entanglement. We further show that the entangled sensor network can be trained to undertake quantum-enhanced data classification tasks.

Original languageEnglish (US)
Title of host publication2021 Optical Fiber Communications Conference and Exhibition, OFC 2021 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781943580866
StatePublished - Jun 2021
Externally publishedYes
Event2021 Optical Fiber Communications Conference and Exhibition, OFC 2021 - San Francisco, United States
Duration: Jun 6 2021Jun 11 2021

Publication series

Name2021 Optical Fiber Communications Conference and Exhibition, OFC 2021 - Proceedings

Conference

Conference2021 Optical Fiber Communications Conference and Exhibition, OFC 2021
Country/TerritoryUnited States
CitySan Francisco
Period6/6/216/11/21

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Hardware and Architecture
  • Signal Processing
  • Electronic, Optical and Magnetic Materials
  • Instrumentation
  • Atomic and Molecular Physics, and Optics

Fingerprint

Dive into the research topics of 'Entangled Sensor Networks Empowered by Machine Learning'. Together they form a unique fingerprint.

Cite this