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Determinating Full Parameters of U-Matrix for Reconfigurable Boson Sampling Circuits using Machine Learning

  • L. X. Wan
  • , H. Zhang
  • , J. G. Huang
  • , G. Zhang
  • , L. C. Kwek
  • , J. Fitzsimons
  • , Y. D. Chong
  • , J. B. Gong
  • , A. Szameit
  • , X. Q. Zhou
  • , M. H. Yung
  • , X. M. Jin
  • , X. L. Su
  • , W. Ser
  • , W. B. Gao
  • , A. Q. Liu

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

Abstract

A method of tuning a reconfigurable silicon photonic circuit into an arbitrary unitary operator with machine learning was proposed to bypass the traditional phase-voltage calibration process and make the prediction of applied heating voltage directly.

Original languageEnglish
Title of host publication2018 Conference on Lasers and Electro-Optics, CLEO 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9781943580422
Publication statusPublished - 6 Aug 2018
Externally publishedYes
Event2018 Conference on Lasers and Electro-Optics, CLEO 2018 - San Jose, United States
Duration: 13 May 2018 → 18 May 2018

Publication series

Name2018 Conference on Lasers and Electro-Optics, CLEO 2018 - Proceedings

Conference

Conference2018 Conference on Lasers and Electro-Optics, CLEO 2018
Country/TerritoryUnited States
CitySan Jose
Period13/05/18 → 18/05/18

ASJC Scopus subject areas

  • Instrumentation
  • Atomic and Molecular Physics, and Optics

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