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Inference and Gradient Measurement for Backpropagation in Photonic Neural Networks

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Abstract

We experimentally demonstrate in situ backpropagation in a programmable nanophotonic interferometer network, achieving inference accuracies matching digital implementations. Error gradients are computed by simultaneously measuring optical interference at intermediate network components, eliminating expensive digital computations.

© 2022 The Author(s)

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