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Conferences > FiO > 2017 > FTh4A > FTh4A.4

Nanophotonic Inverse Design Using Artificial Neural Network

John Peurifoy, Yichen Shen, Yi Yang, Li Jing, Fidel Cano-Renteria, John Joannopoulos, Max Tegmark, and Marin Soljačić

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Abstract

We propose a neural network approach to inverse design nanophotonic objects. Using a fully connected artificial neural network, the method finds the geometry of a spherical nanoparticle that match a desired scattering spectrum - either at a single wavelength, or at a broad-band.

© 2017 Optical Society of America

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