Nanophotonic particle simulation and inverse design using artificial neural networks

• DOI: 10.1126/sciadv.aar4206
• Publication Date: 2018-06-01T18:15:21Z
• Authors: John Peurifoy; Yichen Shen; Li Jing; Yi Yang; Fidel Cano-Renteria; Brendan G. DeLacy; John D. Joannopoulos; Max Tegmark; Marin Soljačić
• Keywords: Nanophotonics

We propose a method to use artificial neural networks approximate light scattering by multilayer nanoparticles. find that the network needs be trained on only small sampling of data simulation high precision. Once is trained, it can simulate such optical processes orders magnitude faster than conventional simulations. Furthermore, used solve nanophotonic inverse design problems using back propagation, where gradient analytical, not numerical.