Experimental reservoir computing with diffractively coupled VCSELs

TL;DR

This paper demonstrates an optical reservoir computing system using 24 diffractively coupled VCSELs, achieving low error rates in memory and pattern recognition tasks, showcasing a novel hardware implementation of RC.

Contribution

It introduces a new experimental setup of reservoir computing with VCSELs coupled via diffraction, advancing optical computing hardware.

Findings

Achieved BER below 1% for XOR and header recognition tasks

Attained RMSE of 0.067 in digital-to-analog conversion

Validated the system's capability for complex computational tasks

Abstract

We present experiments on reservoir computing (RC) using a network of vertical-cavity surface-emitting lasers (VCSELs) that we diffractively couple via an external cavity. Our optical reservoir computer consists of 24 physical VCSEL nodes. We evaluate the system's memory and solve the 2-bit XOR task and the 3-bit header recognition (HR) task with bit error ratios (BERs) below 1\,\% and the 2-bit digital-to-analog conversion (DAC) task with a root-mean-square error (RMSE) of 0.067.