Microring resonators with external optical feedback for time delay reservoir computing

TL;DR

This paper investigates the use of silicon microring resonators with external optical feedback in time delay reservoir computing, demonstrating their versatility and the roles of different nonlinearities in various computational tasks.

Contribution

It provides a detailed numerical analysis of MRRs with external feedback in reservoir computing, highlighting their effectiveness across tasks with diverse memory requirements.

Findings

External feedback significantly enhances performance in high-memory tasks.

Photodetection nonlinearity is crucial for certain chaotic time series predictions.

MRRs can be effectively used in compact, passive photonic reservoir computing systems.

Abstract

Microring resonators (MRRs) are a key photonic component in integrated devices, due to their small size, low insertion losses, and passive operation. While the MRRs have been established for optical filtering in wavelength-multiplexed systems, the nonlinear properties that they can exhibit give rise to new perspectives on their use. For instance, they have been recently considered for introducing optical nonlinearity in photonic reservoir computing systems. In this work, we present a detailed numerical investigation of a silicon MRR operation, in the presence of external optical feedback, in a time delay reservoir computing scheme. We demonstrate the versatility of this compact, passive device, by exploiting different operating regimes and solving computing tasks with diverse memory requirements. We show that when large memory is required, as it occurs in the Narma 10 task, the MRR nonlinearity does not play a significant role when the photodetection nonlinearity is involved, while the contribution of the external feedback is significant. On the contrary, for computing tasks such as the Mackey-Glass and the Santa Fe chaotic timeseries prediction, the MRR and the photodetection nonlinearities contribute both to efficient computation. The presence of optical feedback improves the prediction of the Mackey-Glass timeseries while it plays a minor role in the Santa Fe timeseries case.