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 nonline...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.展开更多
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)。
文摘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.
