A Deep Reinforcement Learning Algorithm for Smart Control of Hysteresis Phenomena in a Mode-Locked Fiber Laser

A Deep Reinforcement Learning Algorithm for Smart Control of Hysteresis Phenomena in a Mode-Locked Fiber Laser

We experimentally demonstrate the application of a double deep Q-learning network algorithm (DDQN) for design of a self-starting fiber mode-locked laser. In contrast to the static optimization of a system design, the DDQN reinforcement algorithm is capable of learning the strategy of dynamic adjustm...

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Bibliographic Details
Main Authors: Alexey Kokhanovskiy, Alexey Shevelev, Kirill Serebrennikov, Evgeny Kuprikov, Sergey Turitsyn
Format: Article
Language:English
Published: MDPI AG 2022-11-01
Series:Photonics
Subjects:
fiber mode-locked lasers
reinforcement learning
hysteresis phenomena
Online Access:https://www.mdpi.com/2304-6732/9/12/921

Internet

https://www.mdpi.com/2304-6732/9/12/921

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