High efficiency metasurface design based on deep generative models

Jiaqi Jiang; David Sell; Jonathan A. Fan

OSA Advanced Photonics Congress (AP) 2019 (IPR, Networks, NOMA, SPPCom, PVLED)
OSA Technical Digest (Optica Publishing Group, 2019),
paper IW1A.5

High efficiency metasurface design based on deep generative models

Jiaqi Jiang, David Sell, and Jonathan A. Fan

Integrated Photonics Research, Silicon and Nanophotonics 2019

Burlingame, California United States
29 July–1 August 2019
ISBN: 978-1-943580-64-4

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Optomechanics and Nanophotonics (IW1A)

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J. Jiang, D. Sell, and J. A. Fan, "High efficiency metasurface design based on deep generative models," in OSA Advanced Photonics Congress (AP) 2019 (IPR, Networks, NOMA, SPPCom, PVLED), OSA Technical Digest (Optica Publishing Group, 2019), paper IW1A.5.

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Abstract

We show that generative neural networks can train from images of periodic, topology-optimized metasurfaces to produce high-efficiency, topologically complex devices, served as a new design tool to facilitate metasurface design.

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