Optimizing Optical Convolution with Nonlinear Absorption

Abstract

Convolution is an essential operation in signal processing and has found applications in convolutional neural networks. All-optical convolution is challenged by small nonlinear coefficients. Two configurations for all-optical convolution with nonlinear absorption are analysed and simulated to identify parameters for optimizing signal-to-noise.