A Novel Reservoir Computing Platform Constructed by Laser Controlled GaAs Resonator

Abstract

In this work, a novel realization of the well known machine learning approach—reservoir computing (RC) using nanoelectromechanical system (NEMS) GaAs resonator is proposed. The specially designed resonator can interact with laser directly without cavity. Thanks to the richness of nonlinearity embedded in the light-mediated dynamical interacting process, the RC platform performs outstandingly even by eliminating the time delay feedback, and the conduction of nonlinear autoregressive moving-average (NARMA) task shows that the normalized mean square error (NMSE) can achieve <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$2.1\,\,\times10$ </tex-math></inline-formula> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−3</sup> that is one order of magnitude lower than the recently reported result. Detailed theoretical modeling as well as numerical simulations on device’s nonlinear dynamics and RC’s hyperparameters are given. The interplay between the transient dynamics of the resonator and RC performance is particularly investigated.