Nanophotonic particle simulation and inverse design using artificial neural networks

See allHide authors and affiliations

Science Advances  01 Jun 2018:
Vol. 4, no. 6, eaar4206
DOI: 10.1126/sciadv.aar4206

You are currently viewing the abstract.

View Full Text


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.

This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license, which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited.

View Full Text