Quantum reservoir computing with classical and nonclassical states in an integrated optical circuit

TL;DR

This paper demonstrates that a quantum reservoir computer using a single nonclassical input state in an integrated optical circuit can significantly outperform classical systems in classification tasks, highlighting a promising approach for quantum-enhanced optical computing.

Contribution

It introduces a simulation method for a bosonic QRC system with nonclassical input states and shows that minimal quantum features can lead to substantial performance improvements.

Findings

Over 9-fold reduction in classification error compared to classical systems

Efficient simulation of quantum optical systems with exact correlation functions

Single nonclassical input mode suffices for quantum advantage

Abstract

Quantum reservoir computing (QRC) is a hardware-implementation-friendly quantum neural network scheme with minimal physical system requirements and a proven advantage over classical counterparts. We use an extension of the positive-P phase space method to efficiently simulate a bosonic, linear silicon-chip based QRC system excited with a single nonclassical state, a "kitten" state. In combination with input-encoding coherent states, our method allows to obtain exact results for all correlation functions without Hilbert space cutoff. Surprisingly, we find that such a setting - where the only "quantumness'' derives from a single input mode, is sufficient to obtain significant (over 9-fold) reduction of classification error over the classical counterpart. Our work provides a promising direction toward efficient quantum computation with accessible optical hardware.