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Acceleration of FDTD-based Inverse Design Using a Neural Network Approach

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Abstract

Instead of using FDTD simulations for all the inverse design steps, we proposed to use neural network-based fitting to estimate the output of the FDTD simulations, and improve the design. We observed clear acceleration in the improvement of metric.

© 2017 Optical Society of America

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