KMS Of Academy of mathematics and systems sciences, CAS
| Data-driven rogue waves and parameter discovery in the defocusing nonlinear Schrodinger equation with a potential using the PINN deep learning | |
| Wang, Li1,2; Yan, Zhenya1,2 | |
| 2021-07-19 | |
| Source Publication | PHYSICS LETTERS A
 |
| ISSN | 0375-9601 |
| Volume | 404Pages:7 |
| Abstract | The physics-informed neural networks (PINNs) can be used to deep learn the nonlinear partial differential equations and other types of physical models. In this paper, we use the multi-layer PINN deep learning method to study the data-driven rogue wave solutions of the defocusing nonlinear Schrodinger (NLS) equation with the time-dependent potential by considering several initial conditions such as the rogue wave, Jacobi elliptic cosine function, two-Gaussian function, or three-hyperbolic-secant function, and periodic boundary conditions. Moreover, the multi-layer PINN algorithm can also be used to learn the parameter in the defocusing NLS equation with the time-dependent potential under the sense of the rogue wave solution. These results will be useful to further discuss the rogue wave solutions of the defocusing NLS equation with a potential in the study of deep learning neural networks. (C) 2021 Elsevier B.V. All rights reserved. |
| Keyword | Defocusing NLS equation with the time-dependent potential Initial-boundary value conditions Physics-informed neural networks Deep learning Data-driven rogue waves and parameter discovery |
| DOI | 10.1016/j.physleta.2021.127408 |
| Indexed By | SCI |
| Language | 英语 |
| Funding Project | National Natural Science Foundation of China[11731014] ; National Natural Science Foundation of China[11925108] |
| WOS Research Area | Physics |
| WOS Subject | Physics, Multidisciplinary |
| WOS ID | WOS:000649676900001 |
| Publisher | ELSEVIER |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.amss.ac.cn/handle/2S8OKBNM/58642 |
| Collection | 中国科学院数学与系统科学研究院 |
| Corresponding Author | Yan, Zhenya |
| Affiliation | 1.Chinese Acad Sci, Acad Math & Syst Sci, Key Lab Math Mechanizat, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Math Sci, Beijing 100049, Peoples R China |
| Recommended Citation GB/T 7714 | Wang, Li,Yan, Zhenya. Data-driven rogue waves and parameter discovery in the defocusing nonlinear Schrodinger equation with a potential using the PINN deep learning[J]. PHYSICS LETTERS A,2021,404:7. |
| APA | Wang, Li,&Yan, Zhenya.(2021).Data-driven rogue waves and parameter discovery in the defocusing nonlinear Schrodinger equation with a potential using the PINN deep learning.PHYSICS LETTERS A,404,7. |
| MLA | Wang, Li,et al."Data-driven rogue waves and parameter discovery in the defocusing nonlinear Schrodinger equation with a potential using the PINN deep learning".PHYSICS LETTERS A 404(2021):7. |
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