Parameters optimization of the beam clean-up system based on stochastic parallel gradient descent method

Sanhong Wang; Junfeng Cui; Haotong Ma; Yonghui Liang; Qifeng Yu

doi:10.1117/12.982001

29 November 2012 Parameters optimization of the beam clean-up system based on stochastic parallel gradient descent method

Sanhong Wang, Junfeng Cui, Haotong Ma, Yonghui Liang, Qifeng Yu

Author Affiliations +

Proceedings Volume 8551, High-Power Lasers and Applications VI; 855113 (2012) https://doi.org/10.1117/12.982001
Event: Photonics Asia, 2012, Beijing, China

Abstract

In a high-energy laser, the thermal aberrations degrade the beam quality and reduce the laser’s output power. Adaptive optics (AO) technique based on a stochastic parallel gradient (SPGD) algorithm can be used to compensate for the distortions in real time to clean up the laser beam. Such a beam clean-up system was simulated and experiments were conducted to study the optimization of the parameters of the gain coefficient and the amplitude of the perturbation. The results show that the convergence property of the SPGD algorithm is improved after the parameters being optimized.

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Sanhong Wang, Junfeng Cui, Haotong Ma, Yonghui Liang, and Qifeng Yu "Parameters optimization of the beam clean-up system based on stochastic parallel gradient descent method", Proc. SPIE 8551, High-Power Lasers and Applications VI, 855113 (29 November 2012); https://doi.org/10.1117/12.982001

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