Modelling self-similar parabolic pulses in optical fibres with a neural network

Sonia Boscolo, John M. Dudley, Christophe Finot

Research output: Contribution to journalArticlepeer-review

Abstract

We expand our previous analysis of nonlinear pulse shaping in optical fibres using machine learning [Opt. Laser Technol., 131 (2020) 106439] to the case of pulse propagation in the presence of gain/loss, with a special focus on the generation of self-similar parabolic pulses. We use a supervised feedforward neural network paradigm to solve the direct and inverse problems relating to the pulse shaping, bypassing the need for direct numerical solution of the governing propagation model.
Original languageEnglish
Article number100066
JournalResults in Optics
Early online date16 Feb 2021
DOIs
Publication statusE-pub ahead of print - 16 Feb 2021

Bibliographical note

Creative Commons Attribution 4.0 International (CC BY 4.0)

Fingerprint

Dive into the research topics of 'Modelling self-similar parabolic pulses in optical fibres with a neural network'. Together they form a unique fingerprint.

Cite this