Deep Neural Networks for the Topological Optimization of Metasurfaces
Paper in proceeding, 2022
We show that a modified CGAN machine learning method that balances the accuracy of desired optical properties with experimental feasibility can solve the free-form inverse design of nanophotonic matasurfaces.
Author
Timo Gahlmann
Chalmers, Physics, Condensed Matter and Materials Theory
Philippe Tassin
Chalmers, Physics, Condensed Matter and Materials Theory
Optics InfoBase Conference Papers
NoM3C.4
9781557528209 (ISBN)
Novel Optical Materials and Applications, NOMA 2022
Maastricht, Netherlands,
Maastricht, Netherlands,
Subject Categories
Language Technology (Computational Linguistics)
Aerospace Engineering
Computational Mathematics
Other Physics Topics