Surrogate-assisted transformation optics inspired GRIN lens design and optimization

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

1 Scopus citations

Abstract

It has been shown that Transformation Optics (TO)-derived gradient-index (GRIN) lenses often outperform more traditional GRIN designs. In order to better understand the origins of this performance improvement, such TO-derived solutions have previously been decomposed into a 2D-polynomial basis, which unveiled the presence of large radial-axial 'cross-term' contributions to the index profile. While these terms are crucial in maximizing the performance of GRIN lenses, finding the optimal index profile becomes a more challenging problem due to the expanded number of input variables. However, this optimization process can be considerably accelerated through the introduction of surrogate models at several stages of the design process.

Original languageEnglish (US)
Title of host publication2017 International Applied Computational Electromagnetics Society Symposium - Italy, ACES 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9780996007832
DOIs
StatePublished - May 1 2017
Event2017 International Applied Computational Electromagnetics Society Symposium - Italy, ACES 2017 - Firenze, Italy
Duration: Mar 26 2017Mar 30 2017

Publication series

Name2017 International Applied Computational Electromagnetics Society Symposium - Italy, ACES 2017

Other

Other2017 International Applied Computational Electromagnetics Society Symposium - Italy, ACES 2017
Country/TerritoryItaly
CityFirenze
Period3/26/173/30/17

All Science Journal Classification (ASJC) codes

  • Radiation
  • Signal Processing
  • Computational Mathematics
  • Instrumentation

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