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Conferences > CLEO_QELS > 2022 > FM5B > FM5B.5

Parity-time Symmetric Optical Neural Networks

Haoqin Deng and Mercedeh Khajavikhan

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Abstract

An optical neural network architecture is proposed that utilizes parity-time symmetric couplers as its building blocks. Gain–loss contrasts across the array are adjusted as a means to train the network.

© 2022 The Author(s)

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