| Issue |
EPJ Web Conf.
Volume 287, 2023
EOS Annual Meeting (EOSAM 2023)
|
|
|---|---|---|
| Article Number | 06001 | |
| Number of page(s) | 2 | |
| Section | Topical Meeting (TOM) 6- Nonlinear and Quantum Optics | |
| DOI | https://doi.org/10.1051/epjconf/202328706001 | |
| Published online | 18 October 2023 | |
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
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