Control of spectral extreme events in ultrafast fiber lasers by a genetic algorithm

Xiuqi Wu, Ying Zhang, Junsong Peng, Sonia Boscolo, Christophe Finot, Heping Zeng

Research output: Contribution to journalArticlepeer-review


Extreme wave events or rogue waves (RWs) are both statistically rare and of exceptionally large amplitude. They are observed in many complex systems ranging from oceanic and optical environments to financial models and Bose–Einstein condensates. As they appear from nowhere and disappear without a trace, their emergence is unpredictable and non-repetitive, which makes them particularly challenging to control. Here, the use of genetic algorithms (GAs), which are exclusively designed for searching and optimizing stationary or repetitive processes in nonlinear optical systems, is extended to the active control of extreme events in a fiber laser cavity. Feeding real-time spectral measurements into a GA controlling the electronics to optimize the cavity parameters, the wave events are able to be triggered in the cavity that have the typical statistics of RWs in the frequency domain. The intensity of the induced RWs can also be tailored. This accurate control enables the generation of optical RWs with a spectral peak intensity 32.8 times higher than the significant intensity threshold. A rationale is proposed and confirmed by numerical simulations of the laser model for the related frequency up- and downshifting of the optical spectrum that are experimentally observed.
Original languageEnglish
Article number2200470
Number of pages11
JournalLaser and Photonics Reviews
Early online date22 Nov 2023
Publication statusE-pub ahead of print - 22 Nov 2023

Bibliographical note

For the purpose of open access, the author has applied a Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version arising


  • machine learning
  • mode locking
  • rogue waves


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