Reservoir computing based on a silicon microring and time multiplexing for binary and analog operations

TL;DR

This paper presents an integrated silicon microring-based reservoir computing system using time multiplexing, demonstrating its capability to perform complex tasks like XOR and Iris classification with potential for scaling.

Contribution

It introduces a novel all-optical reservoir computing scheme using silicon microring and time multiplexing, enabling scalable and efficient reservoir architectures.

Findings

Successfully implemented a reservoir with 50 virtual nodes.

Demonstrated solving delayed XOR and Iris classification tasks.

Showed potential for larger reservoirs with minimal resources.

Abstract

Photonic implementations of reservoir computing (RC) promise to reach ultra-high bandwidth of operation with moderate training efforts. Several optoelectronic demonstrations reported state of the art performances for hard tasks as speech recognition, object classification and time series prediction. Scaling these systems in space and time faces challenges in control complexity, size and power demand, which can be relieved by integrated optical solutions. Silicon photonics can be the disruptive technology to achieve this goal. However, the experimental demonstrations have been so far focused on spatially distributed reservoirs, where the massive use of splitters/combiners and the interconnection loss limits the number of nodes. Here, we propose and validate an all optical RC scheme based on a silicon microring (MR) and time multiplexing. The input layer is encoded in the intensity of a pump beam, which is nonlinearly transferred to the free carrier concentration in the MR and imprinted on a secondary probe. We harness the free carrier dynamics to create a chain-like reservoir topology with 50 virtual nodes. We give proof of concept demonstrations of RC by solving two nontrivial tasks: the delayed XOR and the classification of Iris flowers. This forms the basic building block from which larger hybrid spatio-temporal reservoirs with thousands of nodes can be realized with a limited set of resources.