典型文献
Data-driven parity-time-symmetric vector rogue wave solutions of multi-component nonlinear Schr?dinger equation
文献摘要：
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 Schr?dinger 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 PT 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.
文献关键词：
中图分类号：
作者姓名：
Li-Jun Chang;Yi-Fan Mo;Li-Ming Ling;De-Lu Zeng
作者机构：
School of Mathematics,South China University of Technology,Guangzhou 510640,China
文献出处：
引用格式：
[1]Li-Jun Chang;Yi-Fan Mo;Li-Ming Ling;De-Lu Zeng-.Data-driven parity-time-symmetric vector rogue wave solutions of multi-component nonlinear Schr?dinger equation)[J].中国物理B（英文版）,2022(06):155-162
A类：
Rogue,RWs
B类：
Data,driven,parity,symmetric,vector,rogue,solutions,multi,component,nonlinear,Schr,dinger,equation,waves,are,class,extreme,amplitudes,which,usually,suddenly,disappear,without,any,trace,Recently,PT,NLSE,derived,by,methods,integrable,systems,In,this,paper,we,utilize,stage,physics,informed,neural,networks,PINNs,algorithm,data,coupled,elliptic,shapes,domains,nonzero,boundary,results,experiment,show,that,quite,feasible,effective,physical,above,conditions
AB值：
0.528585
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