Towards Optical Neural Networks with Fabrication Noise Immunity

Michael Y-S. Fang; Michael Y-S. Fang; Sasikanth Manipatruni; Casimir Wierzynski; Amir Khosrowshahi; Ian Young

doi:10.1364/CLEO_SI.2019.SF1N.6

Conference on Lasers and Electro-Optics
OSA Technical Digest (Optica Publishing Group, 2019),
paper SF1N.6
•https://doi.org/10.1364/CLEO_SI.2019.SF1N.6

Towards Optical Neural Networks with Fabrication Noise Immunity

Michael Y-S. Fang, Sasikanth Manipatruni, Casimir Wierzynski, Amir Khosrowshahi, and Ian Young

CLEO: Science and Innovations 2019

San Jose, California United States
5–10 May 2019
ISBN: 978-1-943580-57-6

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AI for Integrated Photonics (SF1N)

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M. Y. Fang, S. Manipatruni, C. Wierzynski, A. Khosrowshahi, and I. Young, "Towards Optical Neural Networks with Fabrication Noise Immunity," in Conference on Lasers and Electro-Optics, OSA Technical Digest (Optica Publishing Group, 2019), paper SF1N.6.

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Abstract

Optical neural networks (ONNs) can provide breakthrough energy/op and latency compared to GP-GPUS/ASICs. Here we compare two different architectures of ONNs and explore the effect of the imprecision of constituent photonic components.

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