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

arXiv: https://arxiv.org/abs/2109.11486 · HTML: https://mlsanity.com/paper/2109.11486/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Sep 2021.

## Built on by (most cited first, 5 of 5)

- [Effects of cavity nonlinearities and linear losses on silicon microring-based reservoir computing](https://mlsanity.com/paper/2310.09433/) (2023)
- [Multi-Task Wavelength-Multiplexed Reservoir Computing Using a Silicon Microring Resonator](https://mlsanity.com/paper/2310.16588/) (2023)
- [Wavelength-multiplexed Delayed Inputs for Memory Enhancement of Microring-based Reservoir Computing](https://mlsanity.com/paper/2312.04204/) (2023)
- [Multi-task Photonic Reservoir Computing: Wavelength Division Multiplexing for Parallel Computing with a Silicon Microring Resonator](https://mlsanity.com/paper/2407.21189/) (2024)
- [Beyond Terabit/s Integrated Neuromorphic Photonic Processor for DSP-Free Optical Interconnects](https://mlsanity.com/paper/2504.15044/) (2025)

## Abstract (arXiv)

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.