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Data-driven parity-time-symmetric vector rogue wave solutions of multi-component nonlinear Schrödinger equation

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摘要 Rogue waves are a class of nonlinear waves with extreme amplitudes,which usually appear suddenly and disappear without any trace.Recently,the parity-time(PT)-symmetric vector rogue waves(RWs)of multi-component nonlinear Schrödinger equation(n-NLSE)are usually derived by the methods of integrable systems.In this paper,we utilize the multi-stage physics-informed neural networks(MS-PINNs)algorithm to derive the data-driven symmetric vector RWs solution of coupled NLS system in elliptic and X-shapes domains with nonzero boundary condition.The results of the experiment show that the multi-stage physics-informed neural networks are quite feasible and effective for multi-component nonlinear physical systems in the above domains and boundary conditions.
作者 Li-Jun Chang Yi-Fan Mo Li-Ming Ling De-Lu Zeng 常莉君;莫一凡;凌黎明;曾德炉(School of Mathematics,South China University of Technology,Guangzhou 510640,China)
机构地区 School of Mathematics
出处 《Chinese Physics B》 SCIE EI CAS CSCD 2022年第6期137-144,共8页 中国物理B(英文版)
基金 supported by National Natural Science Foundation of China(Grant Nos.11771151,61571005,and 61901160) the Science and Technology Program of Guangzhou(Grant No.201904010362) the Fundamental Research Program of Guangdong Province,China(Grant No.2020B1515310023)。
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