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Conferences > CLEO_SI > 2022 > STh5G > STh5G.6

All-optical, ultrafast energy-efficient ReLU function for nanophotonic neural networks

Gordon H.Y. Li, Ryoto Sekine, Rajveer Nehra, Robert M. Gray, Luis Ledezma, Qiushi Guo, and Alireza Marandi

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Abstract

We introduce and experimentally demonstrate an all-optical ReLU nonlinear activation function based on the strong quadratic nonlinearity of lithium niobate nanophotonic waveguides and achieve a record-breaking energy-time product per activation of 1.2 × 10−27 J · s to overcome the nonlinearity bottleneck in photonic neural networks.

© 2022 The Author(s)

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