Effects of cavity nonlinearities and linear losses on silicon microring-based reservoir computing
Bernard J. Giron Castro, Christophe Peucheret, Darko Zibar, Francesco, Da Ros

TL;DR
This paper investigates how cavity nonlinearities and linear losses in silicon microring resonators affect their performance in photonic reservoir computing, identifying optimal conditions for low-error time-series prediction.
Contribution
It provides a numerical analysis of the effects of physical parameters on MRR-based reservoir computing, revealing regimes that optimize prediction accuracy.
Findings
Three distinct operational regions identified based on input power and detuning.
Low-error prediction achieved in a specific low-power, low-node region.
Certain regimes lead to instability or lack of nonlinearity.
Abstract
Microring resonators (MRRs) are promising devices for time-delay photonic reservoir computing, but the impact of the different physical effects taking place in the MRRs on the reservoir computing performance is yet to be fully understood. We numerically analyze the impact of linear losses as well as thermo-optic and free-carrier effects relaxation times on the prediction error of the time-series task NARMA-10. We demonstrate the existence of three regions, defined by the input power and the frequency detuning between the optical source and the microring resonance, that reveal the cavity transition from linear to nonlinear regimes. One of these regions offers very low error in time-series prediction under relatively low input power and number of nodes while the other regions either lack nonlinearity or become unstable. This study provides insight into the design of the MRR and the…
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Taxonomy
TopicsNeural Networks and Reservoir Computing · Photonic and Optical Devices · Optical Network Technologies
