Abstract:
:We propose a method to use artificial neural networks to approximate light scattering by multilayer nanoparticles. We find that the network needs to be trained on only a small sampling of the data to approximate the simulation to high precision. Once the neural network is trained, it can simulate such optical processes orders of magnitude faster than conventional simulations. Furthermore, the trained neural network can be used to solve nanophotonic inverse design problems by using back propagation, where the gradient is analytical, not numerical.
journal_name
Sci Advjournal_title
Science advancesauthors
Peurifoy J,Shen Y,Jing L,Yang Y,Cano-Renteria F,DeLacy BG,Joannopoulos JD,Tegmark M,Soljačić Mdoi
10.1126/sciadv.aar4206subject
Has Abstractpub_date
2018-06-01 00:00:00pages
eaar4206issue
6issn
2375-2548pii
aar4206journal_volume
4pub_type
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