Alessio Lugnan

Performance Enhancement via Synaptic Plasticity in an Integrated Photonic Recurrent Neural Network with Phase-Change Materials

2023

Synaptic plasticity, i.e. the ability of synaptic connections to strengthen or weaken depending on their input, is a fundamental component of learning and memory in biological neural networks [1]. This property allows the network parameters …

Code regarding the article "Reservoir computing with all-optical non-fading memory in a self-pulsing microresonator network"

2024 · arXiv (Cornell University)

Photonic neuromorphic computing may offer promising applications for a broad range of photonic sensors, including optical fiber sensors, to enhance their functionality while avoiding loss of information, energy consumption, and latency due to optical-electrical conversion. …

Photonic Spiking Reservoir Computing Based on a Single Passive Silicon Microring and Time-Wavelength Multiplexing

2025

Spiking artificial neural networks leverage both analog (spike firing time) and digital (spike or quiescent state) processing modalities to efficiently process information through spike sparsity and are widely explored in electronic hardware [1]. In this …