Optically addressed spatial light modulators for photonic neural network implementations

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

doi:10.1117/12.2570607

20 August 2020 Optically addressed spatial light modulators for photonic neural network implementations

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

Proceedings Volume 11469, Emerging Topics in Artificial Intelligence 2020; 1146905 (2020) https://doi.org/10.1117/12.2570607
Event: SPIE Nanoscience + Engineering, 2020, Online Only

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.

Conference Presentation

Citation Download Citation

Vladimir Semenov, Xavier Porte, Maxime Jacquot, Laurent Larger, Ibrahim Abdulhalim, and Daniel Brunner "Optically addressed spatial light modulators for photonic neural network implementations", Proc. SPIE 11469, Emerging Topics in Artificial Intelligence 2020, 1146905 (20 August 2020); https://doi.org/10.1117/12.2570607

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