Optical computing with disorder: random matrix multiplication at the speed of light for machine learning applications

Sylvain Gigan

doi:10.1117/12.2596110

1 August 2021 Optical computing with disorder: random matrix multiplication at the speed of light for machine learning applications

Sylvain Gigan

Author Affiliations +

Proceedings Volume 11804, Emerging Topics in Artificial Intelligence (ETAI) 2021; 118040C (2021) https://doi.org/10.1117/12.2596110
Event: SPIE Nanoscience + Engineering, 2021, San Diego, California, United States

Abstract

Optics is increasingly considered for machine learning, in particular inference, thanks to its intrinsic scalability, speed, and low consumption. Free space implementation are particularly interesting, for instance to implement convolutions or Fourier Transforms. Meanwhile, light propagation of complex media has evolved as a very active field, in particular for imaging. It has been shown that the propagation of a laser through a complex disordered medium is akin to a large size random matrix multiplication, an operation ubiquitous in many instances of signal processing and machine learning . We have recently studied how to exploit such optical implementation of random matrix multiplication for several applications. I will present a few examples for classification, time-series prediction, and for acceleration an Ising Machine.

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Sylvain Gigan "Optical computing with disorder: random matrix multiplication at the speed of light for machine learning applications", Proc. SPIE 11804, Emerging Topics in Artificial Intelligence (ETAI) 2021, 118040C (1 August 2021); https://doi.org/10.1117/12.2596110

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