activity
20152023
most citedPhotonic neural networks based on integrated silicon microresonators

61 citations · 255 across the 11 of their papers we have counts for

collaborators

11 papers

physics.optics2023★ 61 cited

Photonic neural networks based on integrated silicon microresonators

Stefano Biasi, Giovanni Donati, Alessio Lugnan +3

The recent progress of artificial intelligence (AI) has boosted the computational possibilities in fields where standard computers are not able to perform. The AI paradigm is to em…

cs.ET2023★ 1 cited

Nonlinear response of Silicon Photonics microresonators for reservoir computing neural network

Emiliano Staffoli, Davide Bazzanella, Stefano Biasi +4

Nowadays, Information Photonics is extensively studied and sees applications in many fields. The interest in this breakthrough technology is mainly stimulated by the possibility of…

cs.ET2023★ 26 cited

Equalization of a 10 Gbps IMDD signal by a small silicon photonics time delayed neural network

Emiliano Staffoli, Mattia Mancinelli, Paolo Bettotti +1

A small 4-channels time-delayed complex perceptron is used as a silicon photonics neural network (NN) device to compensate for chromatic dispersion in optical fiber links. The NN d…

cs.ET2022★ 20 cited

A Microring as a Reservoir Computing Node: Memory/Nonlinear Tasks and Effect of Input Non-ideality

Davide Bazzanella, Stefano Biasi, Mattia Mancinelli +1

The nonlinear response of an optical microresonator is used in a time multiplexed reservoir computing neural network. Within a virtual node approach combined with an offline traini…

physics.optics2021★ 2 cited

Microring resonators with external optical feedback for time delay reservoir computing

Giovanni Donati, Claudio R. Mirasso, Mattia Mancinelli +2

Microring resonators (MRRs) are a key photonic component in integrated devices, due to their small size, low insertion losses, and passive operation. While the MRRs have been estab…

cs.ET2021★ 27 cited

A photonic complex perceptron for ultrafast data processing

Mattia Mancinelli, Davide Bazzanella, Paolo Bettotti +1

In photonic neural network a key building block is the perceptron. Here, we describe and demonstrate a complex-valued photonic perceptron that combines time and space multiplexing…

physics.comp-ph2021★ 4 cited

PRECISE Photonic hybRid EleCtromagnetIc SolvEr

Davide Bazzanella, Mattia Mancinelli, Massimo Borghi +2

The Photonic hybRid EleCtromagnetic SolvEr (PRECISE) is a Matlab based library to model large and complex photonics integrated circuits. Each circuit is modularly described in term…

physics.optics2021★ 6 cited

A FEM enhanced Transfer Matrix method for optical grating design

Clara Zaccaria, Mattia Mancinelli, Lorenzo Pavesi

A method to design gratings in integrated photonics, is presented. The method is based on a transfer matrix formalism enhanced by Finite Element Method (FEM) parameter calculations…

physics.optics2020★ 59 cited

On the modeling of thermal and free carrier nonlinearities in Silicon On Insulator microring resonators

Massimo Borghi, Davide Bazzanella, Mattia Mancinelli +1

The temporal dynamics of integrated silicon resonators has been modeled using a set of equations coupling the internal energy, the temperature and the free carrier population. Owin…

eess.SP2020

A silicon photonics feed-forward neural network for nonlinear distortion mitigation in an optical link

Mattia Mancinelli, Paolo Bettotti, Lorenzo Pavesi

We design and model a single-layer, passive, all-optical silicon photonics neural network to mitigate optical link nonlinearities. The network nodes are formed by silicon microring…

physics.optics2015★ 49 cited

High frequency electro-optic measurement of strained silicon racetrack resonators

M. Borghi, M. Mancinelli, F. Merget +5

The observation of the electro-optic effect in strained silicon waveguides has been considered as a direct manifestation of an induced non-linearity in the material. In t…