https://doi.org/10.1051/epjconf/202328706019
Predicting frequency comb structure in nonlinear optical fibre using a neural network
1 Aston Institute of Photonic Technologies, Aston University, Birmingham B4 7ET, United Kingdom
2 Université de Franche-Comté, Institut FEMTO-ST, CNRS UMR 6174, Besançon, France
3 Laboratoire Interdisciplinaire CARNOT de Bourgogne, UMR 6303 CNRS-Université de Bourgogne, Dijon, France
* Corresponding author: christophe.finot@u-bourgogne.fr
Published online: 18 October 2023
We deploy a neural network to predict the spectro-temporal evolution of simple sinusoidal temporal modulations upon propagation in a nonlinear dispersive fibre. Thanks to the speed of the neural network, we can efficiently scan the input parameter space for the generation of on-demand frequency combs or the occurrence of substantial spectral/temporal focusing.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
