Integrated optical output layer for a reservoir computer based on frequency multiplexing

Tigers Jonuzi; Alessandro Lupo; Miguel C. Soriano; J. David Domenech Gomez; Serge Massar

doi:10.1117/12.2648744

15 March 2023 Integrated optical output layer for a reservoir computer based on frequency multiplexing

Tigers Jonuzi, Alessandro Lupo, Miguel C. Soriano, J. David Domenech Gomez, Serge Massar

Proceedings Volume 12438, AI and Optical Data Sciences IV; 124380C (2023) https://doi.org/10.1117/12.2648744
Event: SPIE OPTO, 2023, San Francisco, California, United States

Abstract

Reservoir Computers (RCs) are brain-inspired algorithms based on recurrent neural networks where only output weights are tuned, while internal weights remain untrained. We recently demonstrated a photonic frequency-multiplexing RC encoding neurons in the lines of a frequency comb. We also demonstrated a single-layer feed-forward neural network based on a similar frequency-multiplexing principle. Here we present the design for an integrated optical output layer for such frequency multiplexing based photonic neural networks. The all-optical output layer uses wavelength (de)multiplexers and wavelength converters to apply signed weights to neurons encoded in comb lines.

Conference Presentation

Citation Download Citation

Tigers Jonuzi, Alessandro Lupo, Miguel C. Soriano, J. David Domenech Gomez, and Serge Massar "Integrated optical output layer for a reservoir computer based on frequency multiplexing", Proc. SPIE 12438, AI and Optical Data Sciences IV, 124380C (15 March 2023); https://doi.org/10.1117/12.2648744

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