节点文献

可提升被动锁模光纤激光器计算效率的分步傅里叶全局误差局部能量法(英文)

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

  • 推荐 CAJ下载
  • PDF下载
  • 不支持迅雷等下载工具,请取消加速工具后下载。

【作者】 严润彬何晓颖张川张银东饶岚

【Author】 YAN Run-bin;HE Xiao-ying;ZHANG Chuan;ZHANG Yin-dong;RAO Lan;School of Electronic Engineering and Beijing Key Laboratory of Space-Ground Interconnection and Convergence,Beijing University of Posts and Telecommunications;

【通讯作者】 何晓颖;

【机构】 北京邮电大学电子工程学院天地互联与融合北京市重点实验室

【摘要】 本文提出了一种提高被动锁模光纤激光器计算效率的方法,该方法由对称分步傅立叶方法(SSFM)和全局误差局部能量(GELE)方法组成。该方法可将与全局误差相关的局部能量增量限制在一定范围内来控制步长。该方法具有自动步长调整机制。达到同程度的计算精度,本文方法的计算时间为255 s,而小的恒定步长SSFM方法需要3 855 s。这表明本文方法可以将计算效率提高10余倍。本文方法还可以通过RK4IP、Adams、预测-校正等高阶算法进行扩展,以提高精度。

【Abstract】 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 3 855 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.

【基金】 Supported by Foundamental of Research Funds for the Centre Universities (No.2021RC05);National Natural Science Foundation of China (No.61675046, No.61935005)~~
  • 【文献出处】 中国光学(中英文) ,Chinese Optics , 编辑部邮箱 ,2023年03期
  • 【分类号】TN248
  • 【下载频次】17
节点文献中: 

本文链接的文献网络图示:

本文的引文网络