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Microring resonators with external optical feedback for time delay reservoir computing.

Giovanni Donati, Claudio R Mirasso, Mattia Mancinelli

|February 24, 2022

Summary

This summary is machine-generated.

Silicon microring resonators (MRRs) show versatility in photonic reservoir computing. External feedback is crucial for large memory tasks, while both MRR and photodetection nonlinearities aid chaotic time-series prediction.

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Area of Science:

Photonics and Optical Engineering
Nonlinear Optics
Computational Science

Background:

Microring resonators (MRRs) are essential passive photonic components for optical filtering.
Their inherent nonlinear properties offer potential for advanced applications like photonic reservoir computing.
External optical feedback can influence the dynamics and computational capabilities of MRR-based systems.

Purpose of the Study:

To numerically investigate the operation of silicon microring resonators (MRRs) in a time-delay reservoir computing scheme.
To explore the impact of external optical feedback and nonlinearities on MRR performance for diverse computing tasks.
To demonstrate the versatility of MRRs in solving computational problems with varying memory requirements.

Main Methods:

Detailed numerical simulations of silicon MRR operation under external optical feedback.
Implementation of a time-delay reservoir computing framework.
Evaluation of MRR performance on tasks like Narma 10, Mackey-Glass, and Santa Fe chaotic time-series prediction.

Main Results:

For tasks requiring large memory (Narma 10), MRR nonlinearity is less significant than photodetection nonlinearity; external feedback plays a key role.
For chaotic time-series prediction (Mackey-Glass, Santa Fe), both MRR and photodetection nonlinearities contribute to efficient computation.
External optical feedback enhances Mackey-Glass time-series prediction but has a minor effect on Santa Fe time-series prediction.

Conclusions:

Silicon MRRs are versatile devices for photonic reservoir computing, adaptable to different computational demands.
The interplay between MRR nonlinearity, photodetection nonlinearity, and external feedback determines computational efficiency for specific tasks.
MRRs offer a compact and passive solution for complex computing problems, with performance modulated by operating conditions and feedback.