KMS Of Academy of mathematics and systems sciences, CAS
| Deep learning neural networks for the third-order nonlinear Schrodinger equation: bright solitons, breathers, and rogue waves | |
| Zhou, Zijian1,2; Yan, Zhenya1,2 | |
| 2021-10-01 | |
| Source Publication | COMMUNICATIONS IN THEORETICAL PHYSICS
 |
| ISSN | 0253-6102 |
| Volume | 73Issue:10Pages:9 |
| Abstract | The dimensionless third-order nonlinear Schrodinger equation (alias the Hirota equation) is investigated via deep leaning neural networks. In this paper, we use the physics-informed neural networks (PINNs) deep learning method to explore the data-driven solutions (e.g. bright soliton, breather, and rogue waves) of the Hirota equation when the two types of the unperturbated and perturbated (a 2% noise) training data are considered. Moreover, we use the PINNs deep learning to study the data-driven discovery of parameters appearing in the Hirota equation with the aid of bright solitons. |
| Keyword | third-order nonlinear Schrodinger equation deep learning data-driven solitons data-driven parameter discovery |
| DOI | 10.1088/1572-9494/ac1cd9 |
| Indexed By | SCI |
| Language | 英语 |
| Funding Project | National Natural Science Foundation of China[11 925 108] ; National Natural Science Foundation of China[11 731 014] |
| WOS Research Area | Physics |
| WOS Subject | Physics, Multidisciplinary |
| WOS ID | WOS:000692832500001 |
| Publisher | IOP PUBLISHING LTD |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.amss.ac.cn/handle/2S8OKBNM/59193 |
| 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 | Zhou, Zijian,Yan, Zhenya. Deep learning neural networks for the third-order nonlinear Schrodinger equation: bright solitons, breathers, and rogue waves[J]. COMMUNICATIONS IN THEORETICAL PHYSICS,2021,73(10):9. |
| APA | Zhou, Zijian,&Yan, Zhenya.(2021).Deep learning neural networks for the third-order nonlinear Schrodinger equation: bright solitons, breathers, and rogue waves.COMMUNICATIONS IN THEORETICAL PHYSICS,73(10),9. |
| MLA | Zhou, Zijian,et al."Deep learning neural networks for the third-order nonlinear Schrodinger equation: bright solitons, breathers, and rogue waves".COMMUNICATIONS IN THEORETICAL PHYSICS 73.10(2021):9. |
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