Scalable photonic platform for real-time quantum reservoir computing

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.

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• Quantum reservoir computing in Jaynes-Cummings models: Nonlinear memory and time-series prediction
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