Memory Capacity Analysis of Time-delay Reservoir Computing Based on Silicon Microring Resonator Nonlinearities
Bernard J. Giron Castro, Christophe Peucheret, Francesco Da Ros

TL;DR
This paper analyzes the nonlinear and linear memory capacity of silicon microring resonator-based time-delay reservoir computing, focusing on how physical properties influence performance and stability in photonic RC systems.
Contribution
It provides a detailed quantification of the memory capacity related to nonlinear effects and physical parameters of silicon microring resonators in TDRC.
Findings
Memory capacity depends on carrier lifetime and thermo-optic effects.
Optimal nonlinearities balance performance and stability.
Parameter space for effective RC operation is characterized.
Abstract
Silicon microring resonators (MRRs) have shown strong potential in acting as the nonlinear nodes of photonic reservoir computing (RC) schemes. By using nonlinearities within a silicon MRR, such as the ones caused by free-carrier dispersion (FCD) and thermo-optic (TO) effects, it is possible to map the input data of the RC to a higher dimensional space. Furthermore, by adding an external waveguide between the through and add ports of the MRR, it is possible to implement a time-delay RC (TDRC) with enhanced memory. The input from the through port is fed back into the add port of the ring with the delay applied by the external waveguide effectively adding memory. In a TDRC, the nodes are multiplexed in time, and their respective time evolutions are detected at the drop port. The performance of MRR-based TDRC is highly dependent on the amount of nonlinearity in the MRR. The nonlinear…
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Taxonomy
TopicsNeural Networks and Reservoir Computing · Advanced Memory and Neural Computing · Neural Networks and Applications
