Silicon Ring Resonator with Phase-Change Material as a Plastic Dynamical Node for Scalable All-Optical Neural Networks with Synaptic Plasticity

Lugnan, AlessioAlessioLugnanCarrillo, Santiago Garcia-CuevasSantiago Garcia-CuevasCarrilloSong, JunchaoJunchaoSongAggarwal, SamarthSamarthAggarwalBruckerhoff-Pluckelmann, FrankFrankBruckerhoff-PluckelmannPernice, Wolfram H. P.Wolfram H. P.PerniceBhaskaran, HarishHarishBhaskaranWright, C. DavidC. DavidWrightBienstman, PeterPeterBienstman2026-05-042026-05-0420232162-7339https://imec-publications.be/handle/20.500.12860/59298Synaptic plasticity, that is the ability of connections in neural networks to strengthen or weaken depending on their input, is a fundamental component of learning and memory in biological brains. We present a numerical and experimental investigation of an integrated photonic plastic node, consisting of a silicon ring resonator enhanced by phase-change materials (GST). This all-optical device is capable of dynamical nonlinear behaviour, multi-scale volatile memory, non-volatile memory and multi-wavelength operations. We propose its employment as a building block in scalable all-optical dynamical neural networks that can adapt to their input via synaptic plasticity.engSilicon Ring Resonator with Phase-Change Material as a Plastic Dynamical Node for Scalable All-Optical Neural Networks with Synaptic PlasticityProceedings paper10.1109/icton59386.2023.10207385WOS:001572095100171