Optically addressed spatial light modulators for photonic neural network implementations

Vladimir Semenov, Xavier Porte, Maxime Jacquot, Laurent Larger, Ibrahim Abdulhalim, Daniel Brunner

Research output: Non-textual formDigital or Visual Products

Abstract

We propose a novel implementation of autonomous photonic neural networks based on optically-addressed spatial light modulators (OASLMs). In our approach, the OASLM operates as a spatially non-uniform birefringent waveplate, the retardation of which nonlinearly depends on the incident light intensity. We develop a complete electrical and optical model of the device and investigate the optimal operational characteristics. We study both, feed-forward and recurrent neural networks and demonstrate that OASLMs are promising candidates for the implement of autonomous photonic neural networks with large numbers of neurons and ultra low energy consumption.
Original languageEnglish
PublisherSPIE
DOIs
StatePublished - 20 Aug 2020

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