Global Optimization and Deep Learning Techniques For Freeform Nanophotonic Metadevices

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

Abstract

Engineered freeform components are advancing the state of the art in the field of nanophotonics. To this end, optical metasurfaces are increasingly desirable due to their ability to control the phase, magnitude, and polarization of transmitted (and/or reflected) light and improvements in nanofabrication techniques. While metasurfaces have demonstrated unprecedented control over optical performances, it is not well understood how to determine the geometries necessary to achieve a targeted optical performance. That being so, optimization and inverse-design techniques have proven invaluable to engineers seeking to realize metadevices with specific targeted functionalities. In this presentation, we discuss the advantages of our metadevice design process which utilizes a combination of global optimization and deep learning to realize an accelerated mutliobjective framework for generating highly performant designs that are robust to fabrication uncertainties.

Original languageEnglish (US)
Title of host publication2023 International Applied Computational Electromagnetics Society Symposium, ACES-Monterey 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781733509633
DOIs
StatePublished - 2023
Event2023 International Applied Computational Electromagnetics Society Symposium, ACES-Monterey 2023 - Monterey, United States
Duration: Mar 26 2023Mar 30 2023

Publication series

Name2023 International Applied Computational Electromagnetics Society Symposium, ACES-Monterey 2023

Conference

Conference2023 International Applied Computational Electromagnetics Society Symposium, ACES-Monterey 2023
Country/TerritoryUnited States
CityMonterey
Period3/26/233/30/23

All Science Journal Classification (ASJC) codes

  • Computational Mathematics
  • Instrumentation
  • Radiation
  • Computer Networks and Communications
  • Signal Processing

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