Reservoir computing with all-optical non-fading memory in a self-pulsing microresonator network

TL;DR

This paper demonstrates a passive all-optical reservoir computing system using silicon microring resonators that can retain information for tens of microseconds, enabling multi-timescale signal processing without energy loss.

Contribution

It introduces the first physical reservoir computing implementation with non-fading memory in a passive silicon microring network for multi-timescale processing.

Findings

Capable of retaining input information for tens of microseconds.

Successfully infers timing of input pulses and spike rates after delays.

Operates effectively at two different timescales with a fivefold difference.

Abstract

Photonic neuromorphic computing may offer promising applications for a broad range of photonic sensors, including optical fiber sensors, to enhance their functionality while avoiding loss of information, energy consumption, and latency due to optical-electrical conversion. However, time-dependent sensor signals usually exhibit much slower timescales than photonic processors, which also generally lack energy-efficient long-term memory. To address this, we experimentally demonstrate a first implementation of physical reservoir computing with non-fading memory for multi-timescale signal processing. This is based on a fully passive network of 64 coupled silicon microring resonators. Our compact photonic reservoir is capable of hosting energy-efficient nonlinear dynamics and multistability. It can process and retain input signal information for an extended duration, at least tens of microseconds. Our reservoir computing system can learn to infer the timing of a single input pulse and the spike rate of an input spike train, even after a relatively long period following the end of the input excitation. We demonstrate this operation at two different timescales, with approximately a factor of 5 difference. This work presents a novel approach to extending the memory of photonic reservoir computing and its timescale of application.