Use of neural networks fro designing robust flat-optics on flexible substrates

F. Getman, M. Makarenko, Q. Wang, A. Burguete-Lopez, A. Fratalocchi*

*Corresponding author for this work

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

Abstract

We present an inverse design platform that enables the fast design of flexible flat-optics that maintain high performance under deformations. The platform is based on evolutionary large-scale optimizers, and neural network predictors.

Original languageEnglish (US)
Title of host publication2022 Conference on Lasers and Electro-Optics, CLEO 2022 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781957171050
StatePublished - 2022
Event2022 Conference on Lasers and Electro-Optics, CLEO 2022 - San Jose, United States
Duration: May 15 2022May 20 2022

Publication series

Name2022 Conference on Lasers and Electro-Optics, CLEO 2022 - Proceedings

Conference

Conference2022 Conference on Lasers and Electro-Optics, CLEO 2022
Country/TerritoryUnited States
CitySan Jose
Period05/15/2205/20/22

Bibliographical note

Publisher Copyright:
© Optica Publishing Group 2022, © 2022 The Author(s)

ASJC Scopus subject areas

  • Instrumentation
  • Spectroscopy
  • Biomedical Engineering
  • Electrical and Electronic Engineering
  • Management, Monitoring, Policy and Law
  • Materials Science (miscellaneous)
  • Acoustics and Ultrasonics
  • Atomic and Molecular Physics, and Optics

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