Cavity Solitons as a Nonlinear Substrate for Photonic Neuromorphic Computing
Optics
2026-05-20 v2
Abstract
Reservoir computing leverages nonlinear dynamics of physical systems to process temporal information with minimal training cost. Here, we demonstrate that cavity solitons sustained in a fiber optical cavity provide an optical platform for photonic reservoir computing. Our methodology exploits the use of a phase-modulated drive laser to encode the input, while the reservoir states are accessed through frequency-resolved readout. Numerical simulations indicate that the emission of Kelly waves enriches the dynamics and enhances performance for machine learning tasks. We evaluate the performance of the cavity-soliton reservoir computer on several standard benchmark tasks.
Cite
@article{arxiv.2602.18110,
title = {Cavity Solitons as a Nonlinear Substrate for Photonic Neuromorphic Computing},
author = {Amir Arsalan Arabieh and Alessandro Lupo and Simon-Pierre Gorza and Serge Massar},
journal= {arXiv preprint arXiv:2602.18110},
year = {2026}
}