Coherent beam combination based on Q-learning algorithm
Autor: | Xi Zhang, Shun Li, Pingxue Li, Chunyong Li, Chuanfei Yao, Xueyan Dong, Yunchen Zhu, Luo Wang |
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Rok vydání: | 2021 |
Předmět: |
Computer Science::Machine Learning
business.industry Computer science Stability (learning theory) 02 engineering and technology 021001 nanoscience & nanotechnology Laser 01 natural sciences Atomic and Molecular Physics and Optics Field (computer science) Electronic Optical and Magnetic Materials Power (physics) law.invention 010309 optics Optics law 0103 physical sciences Reinforcement learning Electrical and Electronic Engineering Physical and Theoretical Chemistry 0210 nano-technology Gradient descent business Algorithm Beam (structure) |
Zdroj: | Optics Communications. 490:126930 |
ISSN: | 0030-4018 |
Popis: | Coherent beam combination (CBC) is an effective method to break the limiting power of a single fiber laser. The Q-learning algorithm is one of the reinforcement learning algorithms. We use the Q-learning algorithm to do phase compensation in the field of CBC. The performance difference between the Q-learning algorithm and the stochastic parallel gradient descent optimization algorithm (SPGD) is analyzed by simulating time-domain coherent synthesis. The results show that the Q-learning algorithm is easier to debug and has better stability. |
Databáze: | OpenAIRE |
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