Data-driven rogue waves and parameters discovery in nearly integrable \(\mathcal{PT}\)-symmetric Gross-Pitaevskii equations via PINNs deep learning
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Publication:2167994
DOI10.1016/j.physd.2022.133430zbMath1496.35373OpenAlexW4288032460WikidataQ113866764 ScholiaQ113866764MaRDI QIDQ2167994
Shou-Fu Tian, Zhenya Yan, Ming Zhong, Shibo Gong
Publication date: 1 September 2022
Published in: Physica D (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.physd.2022.133430
generalized Gross-Pitaevskii equationcomplex \(\mathcal{PT}\)-symmetric potentialsdata-driven rogue waves and parameters discoveryphysics-informed deep neural networks
Artificial neural networks and deep learning (68T07) PDEs in connection with fluid mechanics (35Q35) Water waves, gravity waves; dispersion and scattering, nonlinear interaction (76B15) Inverse problems for PDEs (35R30) NLS equations (nonlinear Schrödinger equations) (35Q55)
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Uses Software
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