Reinforcement Learning for Efficient Identification of Soliton System Parameters Across Expansive Domains  

作　　者：Cheng Hu Zhiyang Zhang Muwei Liu Liuyu Xiang Huijia Wu Wenjun Liu Zhaofeng He 

机构地区：[1]State Key Laboratory of Information Photonics and Optical Communications,School of Science,Beijing University of Posts and Telecommunications,Beijing 100876,China [2]School of Artificial Intelligence,Beijing University of Posts and Telecommunications,Beijing 100876,China [3]Beijing Laser Creation Optoelectronics Technology Company Limited,Beijing 101400,China

出　　处：《Chinese Physics Letters》2024年第12期20-29,共10页中国物理快报（英文版）

基　　金：National Key Research and Development Program of China(Grant No.2022YFA1604200);Beijing Municipal Science and Technology Commission,Administrative Commission of Zhongguancun Science Park(Grant No.Z231100006623006).

摘　　要：Optical solitons in mode-locked fiber lasers and optical communication links have various applications. Thestudy of transmission modes of optical solitons necessitates the investigation of the relationship between theequation parameters and soliton evolution employing deep learning techniques. However, the existing identificationmodels exhibit a limited parameter domain search range and are significantly influenced by initialization.Consequently, they often result in divergence toward incorrect parameter values. This study harnessed reinforcementlearning to revamp the iterative process of the parameter identification model. By developing a two-stageoptimization strategy, the model could conduct an accurate parameter search across arbitrary domains. Theinvestigation involved several experiments on various standard and higher-order equations, illustrating that theinnovative model overcame the impact of initialization on the parameter search, and the identified parametersare guided toward their correct values. The enhanced model markedly improves the experimental efficiency andholds significant promise for advancing the research of soliton propagation dynamics and addressing intricatescenarios.

关 键 词：SOLITON PARAMETER SOLITONS 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] O437[自动化与计算机技术—控制科学与工程]