Neural Networks Based on Ultrafast Time-Delayed Effects in Exciton Polaritons

Abstract

We demonstrate that time-delayed nonlinear effects in exciton polaritons can be used to construct neural networks where information is coded in optical pulses arriving consecutively on the sample. The highly nonlinear effects are induced by time-dependent interactions with the excitonic reservoir. These nonlinearities allow the creation of a nonlinear XOR logic gate that can perform operations on the picosecond timescale. An optoelectronic neural network based on the constructed logic gate performs the classification of spoken digits with a high accuracy rate.