Volume 16 Issue 3
May  2023
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YAN Run-bin, HE Xiao-ying, ZHANG Chuan, ZHANG Yin-dong, RAO Lan. SSFM-global-error-local-energy method for improving computational efficiency of passively mode-locked fiber laser[J]. Chinese Optics, 2023, 16(3): 733-742. doi: 10.37188/CO.EN.2022-0016
Citation: YAN Run-bin, HE Xiao-ying, ZHANG Chuan, ZHANG Yin-dong, RAO Lan. SSFM-global-error-local-energy method for improving computational efficiency of passively mode-locked fiber laser[J]. Chinese Optics, 2023, 16(3): 733-742. doi: 10.37188/CO.EN.2022-0016

SSFM-global-error-local-energy method for improving computational efficiency of passively mode-locked fiber laser

doi: 10.37188/CO.EN.2022-0016
Funds:  Supported by Foundamental of Research Funds for the Centre Universities (No.2021RC05); National Natural Science Foundation of China (No.61675046, No.61935005)
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  • Author Bio:

    YAN Run-bin (1998—), male, born in Kunming, Yunnan Province, master student. He received hisbachelor’s degree from Beijing University of Posts and Telecommunications in 2020. He is mainly engaged in the research of mode-locked fiber laser and nonlinear optics. E-mail:yanrunbin@bupt.edu.cn

    HE Xiao-ying (1981—), female, born in Jingzhou, Hubei Province, Ph.D., associate research fellow. She received her Ph.D. from Huazhong University of Science and Technology in 2009. She is mainly engaged in the research of semiconductor lasers, fiber lasers, graphene optoelectronic devices and other novel optoelectronic devices. E-mail:xiaoyinghe@bupt.edu.cn

  • Corresponding author: xiaoyinghe@bupt.edu.cn
  • Received Date: 20 Sep 2022
  • Rev Recd Date: 24 Oct 2022
  • Accepted Date: 22 Nov 2022
  • Available Online: 30 Dec 2022
  • We propose a method for improving the computational efficiency of passively mode-locked fiber laser, which is composed by Symmetric Split-step Fourier Method (SSFM) and the Global-Error-Local-Energy (GELE) method for solving propagating equations. Our proposed method relies on the limitation of local energy increment related with global error within a certain value to control the selection of step size. This method has advantage of an automatic step adjustment mechanism. To achieve the same order of computation accuracy, the computational time of our method is 255 s, while SSFM with small constant step size method needs to calculate 3855 s. The computational time of our proposed method is one or two orders of magnitude less than that of the SSFM, which indicates our method can enhance the computational efficiency by a factor up to 10. It could be expanded with high-order algorithms, such as the fourth-order Runge-Kutta in the interaction picture (RK4IP), Adams, predictor–corrector, etc. for improving the accuracy.

     

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