On-chip online learning and inference for photonic pattern recognition

Bicky A. Marquez, Zhimu Guo, Hugh Morison, Sudip Shekhar, Lukas Chrostowski, Paul Prucnal, Bhavin J. Shastri

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

Abstract

Recent investigations in neuromorphic photonics exploits photonics for neuron models. Here, we experimentally demonstrate a silicon photonic chip that can perform training and testing of a Hopfield network to reconstruct corrupted input patterns.

Original languageEnglish (US)
Title of host publicationCLEO
Subtitle of host publicationScience and Innovations, CLEO:S and I 2021
PublisherThe Optical Society
ISBN (Electronic)9781557528209
StatePublished - 2021
EventCLEO: Science and Innovations, CLEO:S and I 2021 - Part of Conference on Lasers and Electro-Optics, CLEO 2021 - Virtual, Online, United States
Duration: May 9 2021May 14 2021

Publication series

NameOptics InfoBase Conference Papers

Conference

ConferenceCLEO: Science and Innovations, CLEO:S and I 2021 - Part of Conference on Lasers and Electro-Optics, CLEO 2021
Country/TerritoryUnited States
CityVirtual, Online
Period5/9/215/14/21

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Mechanics of Materials

Fingerprint

Dive into the research topics of 'On-chip online learning and inference for photonic pattern recognition'. Together they form a unique fingerprint.

Cite this