GRIN lens design through the use of surrogate models based on Zernike aberrations

John A. Easum, Jogender Nagar, Sawyer D. Campbell, Douglas H. Werner

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

Abstract

In this paper, we present a computational method for rapidly designing GRadient-INdex (GRIN) lenses by employing a surrogate model that relates input lens parameters to output Zernike aberrations. This approach also provides a path forward for the designer to identify which lens parameters have the largest impact on specific aberrations. Through the use of orthogonal Latin Hypercube Sampling (LHS) and multivariate polynomial regressions, a surrogate model is trained to approximate the ray trace evaluations. Finally, a plano-convex GRIN lens based on Silicon-Germanium mixing is optimized using both full ray trace and surrogate model evaluations. A ∼40× speed improvement is realized with the surrogate-assisted optimization while achieving similar optical performance.

Original languageEnglish (US)
Title of host publication2016 IEEE Antennas and Propagation Society International Symposium, APSURSI 2016 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages573-574
Number of pages2
ISBN (Electronic)9781509028863
DOIs
StatePublished - Oct 25 2016
Event2016 IEEE Antennas and Propagation Society International Symposium, APSURSI 2016 - Fajardo, Puerto Rico
Duration: Jun 26 2016Jul 1 2016

Publication series

Name2016 IEEE Antennas and Propagation Society International Symposium, APSURSI 2016 - Proceedings

Other

Other2016 IEEE Antennas and Propagation Society International Symposium, APSURSI 2016
CountryPuerto Rico
CityFajardo
Period6/26/167/1/16

All Science Journal Classification (ASJC) codes

  • Instrumentation
  • Radiation
  • Computer Networks and Communications

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