Scalable photonic platform for real-time quantum reservoir computing

TL;DR

This paper presents a scalable photonic platform for real-time quantum reservoir computing, addressing challenges in quantum advantage and noise, and proposing strategies for system scaling with current technology.

Contribution

It introduces a practical photonic setup for quantum reservoir computing capable of real-time processing and discusses methods to maintain performance as the system scales.

Findings

Ideal operation achieves maximum capacities.

Statistical noise undermines quantum advantage.

Proposed strategy sustains performance during scaling.

Abstract

Quantum Reservoir Computing (QRC) exploits the information processing capabilities of quantum systems to solve non-trivial temporal tasks, improving over their classical counterparts. Recent progress has shown the potential of QRC exploiting the enlarged Hilbert space, but real-time processing and the achievement of a quantum advantage with efficient use of resources are prominent challenges towards viable experimental realizations. In this work, we propose a photonic platform suitable for real-time QRC based on a physical ensemble of reservoirs in the form of identical optical pulses recirculating through a closed loop. While ideal operation achieves maximum capacities, statistical noise is shown to undermine a quantum advantage. We propose a strategy to overcome this limitation and sustain the QRC performance when the size of the system is scaled up. The platform is conceived for experimental implementations to be viable with current technology.