Multimode fiber modal decomposition based on hybrid genetic global optimization algorithm

Lei Li; Jinyong Leng; Pu Zhou; Jinbao Chen

doi:10.1117/12.2284903

24 October 2017 Multimode fiber modal decomposition based on hybrid genetic global optimization algorithm

Lei Li, Jinyong Leng, Pu Zhou, Jinbao Chen

Proceedings Volume 10457, AOPC 2017: Laser Components, Systems, and Applications; 104572K (2017) https://doi.org/10.1117/12.2284903
Event: Applied Optics and Photonics China (AOPC2017), 2017, Beijing, China

Abstract

Numerical modal decomposition (MD) is an effective approach to reveal modal characteristics in high power fiber lasers. The main challenge is to find a suitable multi-dimensional optimization algorithm to reveal exact superposition of eigenmodes, especially for multimode fiber. A novel hybrid genetic global optimization algorithm, named GA-SPGD, which combines the advantages of genetic algorithm (GA) and stochastic parallel gradient descent (SPGD) algorithm, is firstly proposed to reduce local minima possibilities from sensitivity initial values. Firstly, GA is applied to search the rough global optimization position based on near-far-field intensity distribution with high accuracy. Upon those initial values, SPGD algorithm is afterwards used to find the exact optimization values based on near-field intensity distribution with fast convergence speed. Numerical simulations validate the feasibility and reliability.

Citation Download Citation

Lei Li, Jinyong Leng, Pu Zhou, and Jinbao Chen "Multimode fiber modal decomposition based on hybrid genetic global optimization algorithm", Proc. SPIE 10457, AOPC 2017: Laser Components, Systems, and Applications, 104572K (24 October 2017); https://doi.org/10.1117/12.2284903

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