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Control of Spectral Extreme Events in Ultrafast Fiber Lasers by a Genetic Algorithm
Authors:Xiuqi Wu  Ying Zhang  Junsong Peng  Sonia Boscolo  Christophe Finot  Heping Zeng
Institution:1. State Key Laboratory of Precision Spectroscopy, East China Normal University, Shanghai, 200062 China;2. Aston Institute of Photonic Technologies, Aston University, Aston Triangle, Birmingham, B4 7ET UK;3. Laboratoire Interdisciplinaire Carnot de Bourgogne, UMR 6303 CNRS – Université de Bourgogne Franche-Comté, Dijon, F-21078 CEDEX France
Abstract: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.
Keywords:machine learning  mode locking  rogue waves
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