https://doi.org/10.1051/epjconf/202328706001
Machine learning control of complex nonlinear dynamics in fibre lasers - INVITED
1 Aston Institute of Photonic Technologies, Aston University, Birmingham B4 7ET, United Kingdom
2 State Key Laboratory of Precision Spectroscopy, East China Normal University, Shanghai 200062, China
3 Laboratoire Interdisciplinaire Carnot de Bourgogne, UMR 6303 CNRS-Université de Bourgogne, 21078 Dijon Cedex, France
* e-mail: s.a.boscolo@aston.ac.uk
Published online: 18 October 2023
We review our recent work on the use of genetic algorithms to control non-stationary nonlinear wave dynamics in ultrafast fibre lasers, including the generation of breathing-soliton dynamics with controlled characteristics, the disclosure of the fractal dynamics of breathers, and the generation of rogue waves with controlled intensity.
© 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.
