Nanophotonic particle simulation and inverse design using artificial neural networks.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 29868640.
- Also identified by DOI 10.1126/sciadv.aar4206 and PMC identifier 5983917.
- Licence recorded as CC BY-NC.
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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.