Gaussian states of continuous-variable quantum systems provide universal and versatile reservoir computing

Abstract

Most attempts to delineate quantum machine-learning-related computing capabilities of continuous variables states have relied on non-Gaussian resources. Here, the authors show that linear systems with continuous-variable Gaussian states are a promising platform for the implementation of quantum reservoir computers with universal approximation capabilities