Photonic Neural Network Fabricated on Thin Film Lithium Niobate for High-Fidelity and Power-Efficient Matrix Computation

  • Yong Zheng
  • , Rongbo Wu
  • , Yuan Ren
  • , Rui Bao
  • , Jian Liu
  • , Yu Ma
  • , Min Wang
  • , Ya Cheng*
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We present here the first implementation of a photonic neural network based on the thin-film lithium niobate platform. Our device features ultra-high fidelity as 98.5% and exceptional power efficiency as 33.5 fJ per operation.

Original languageEnglish
Title of host publication16th Pacific Rim Conference on Lasers and Electro-Optics, CLEO-PR 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350372076
DOIs
StatePublished - 2024
Event16th Pacific Rim Conference on Lasers and Electro-Optics, CLEO-PR 2024 - Incheon, Korea, Republic of
Duration: 4 Aug 20249 Aug 2024

Publication series

Name16th Pacific Rim Conference on Lasers and Electro-Optics, CLEO-PR 2024

Conference

Conference16th Pacific Rim Conference on Lasers and Electro-Optics, CLEO-PR 2024
Country/TerritoryKorea, Republic of
CityIncheon
Period4/08/249/08/24

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