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Conferences > CLEO_SI > 2022 > SW5E > SW5E.6

Finding the Right Deep Neural Network Model for Efficient Design of Tunable Nanophotonic Devices

Minwoo Jung, Keisuke Kojima, Toshiaki Koike-Akino, Ye Wang, Dayu Zhu, and Matthew Brand

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Abstract

We develop generative deep neural networks that explore relevant statistical structures to expedite a complex inverse design of nanophotonic on-chip wavelength de-multiplexer. Our design, targeting at telecomm-wavelengths, is electrically switchable via liquid crystal tuning.

© 2022 The Author(s)

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