Robustness Optimization of Nanophotonic Devices Using Deep Learning

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

Abstract

Realizing state-of-the-art metasurfaces depends on meeting strict geometric tolerances due to their inherent sensitivity to structural variations. A design may have extremely good performance in simulation which is lost when undergoing fabrication. We present how a Deep Learning-augmented multiobjective optimization method can be used for designing metasurfaces which are robust to a common type of manufacturing defect, namely erosion and dilation.

Original languageEnglish (US)
Title of host publication2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages487-488
Number of pages2
ISBN (Electronic)9781665496582
DOIs
StatePublished - 2022
Event2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022 - Denver, United States
Duration: Jul 10 2022Jul 15 2022

Publication series

Name2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022 - Proceedings

Conference

Conference2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022
Country/TerritoryUnited States
CityDenver
Period7/10/227/15/22

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Signal Processing
  • Instrumentation

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