Fading Memory and Nonlinear Dynamics in a Microring Resonator Network and their Use in Computation
Abstract
Silicon microring resonators are promising components for photonic reservoir computing because their nonlinear optical response can transform signals and retain information about recent inputs. Under constant optical excitation, their coupled free-carrier and thermal dynamics can generate self-pulsing: a periodic output response. However, constant-input behavior does not reveal how these dynamics respond to randomly modulated signals or whether their memory is useful for temporal processing. Here, we characterize a single silicon microring resonator and a passive network of microring resonators under random input modulation. The temporal component associated with self-pulsing remains observable under random modulation, but the largest fading memory occurs near the self-pulsing boundary, where no resolved self-pulsing-like oscillation is present. reservoir computing metrics, such as memory capacity, map this accessible memory, and its decay provides effective timescales associated mainly with free-carrier and thermal relaxation. Finally, we use NARMA reconstruction to test whether the measured memory profile supports nonlinear temporal processing. Responses with a resolved self-pulsing-like component perform worse on this task, and the intrinsic memory profile is not matched to the required input history. These results show that reservoir computing metrics can characterize nonlinear microring resonator dynamics even when the physical system is not an effective standalone reservoir for the selected task.
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BibTeX
@misc{foradori2026fading,
title = {{Fading Memory and Nonlinear Dynamics in a Microring Resonator Network and their Use in Computation}},
author = {Alessandro Foradori and Alessio Lugnan and Lorenzo Pavesi and Peter Bienstman},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.16432},
eprint = {2610.16432},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.16432},
}
RIS
TY - UNPB
TI - Fading Memory and Nonlinear Dynamics in a Microring Resonator Network and their Use in Computation
AU - Alessandro Foradori
AU - Alessio Lugnan
AU - Lorenzo Pavesi
AU - Peter Bienstman
PY - 2026
DA - 2026/10/12
PB - arXiv
DO - 10.48550/arxiv.2610.16432
UR - https://arxiv.org/abs/2610.16432
AB - Silicon microring resonators are promising components for photonic reservoir computing because their nonlinear optical response can transform signals and retain information about recent inputs. Under constant optical excitation, their coupled free-carrier and thermal dynamics can generate self-pulsing: a periodic output response. However, constant-input behavior does not reveal how these dynamics respond to randomly modulated signals or whether their memory is useful for temporal processing. Here, we characterize a single silicon microring resonator and a passive network of microring resonators under random input modulation. The temporal component associated with self-pulsing remains observable under random modulation, but the largest fading memory occurs near the self-pulsing boundary, where no resolved self-pulsing-like oscillation is present. reservoir computing metrics, such as memory capacity, map this accessible memory, and its decay provides effective timescales associated mainly with free-carrier and thermal relaxation. Finally, we use NARMA reconstruction to test whether the measured memory profile supports nonlinear temporal processing. Responses with a resolved self-pulsing-like component perform worse on this task, and the intrinsic memory profile is not matched to the required input history. These results show that reservoir computing metrics can characterize nonlinear microring resonator dynamics even when the physical system is not an effective standalone reservoir for the selected task.
ER -