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Revisiting the dynamics of Bose-Einstein condensates in a double well by deep learning with a hybrid network

Full title: Revisiting the dynamics of Bose-Einstein condensates in a double well by deep learning with a hybrid network

Author/creator: Li, Shurui, Xu, Jianqin, Qian, Jing, Zhang, Weiping.

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Record Identifier: TN_cdi_proquest_journals_2574778415

Language: English

Formats: Articles

Publishers: Beijing: Higher Education Press

Permalink: https://collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2574778415

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    Revisiting the dynamics of Bose-Einstein condensates in a double well by deep learning with a hybrid network

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    TN_cdi_proquest_journals_2574778415

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    https://collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2574778415

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    Revisiting the dynamics of Bose-Einstein condensates in a double well by deep learning with a hybrid network

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    Revisiting the dynamics of Bose-Einstein condensates in a double well by deep learning with a hybrid network

    Full title

    Revisiting the dynamics of Bose-Einstein condensates in a double well by deep learning with a hybrid network

    Author / Creator

    Li, Shurui ; Xu, Jianqin ; Qian, Jing ; Zhang, Weiping

    Publisher

    Beijing: Higher Education Press

    Journal title

    Frontiers of physics, 2022, Vol.17 (2), p.22504

    Record Identifier

    TN_cdi_proquest_journals_2574778415

    Language

    English

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    Articles

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    Analysis Astronomy Astrophysics and Cosmology Atomic Bose-Einstein condensates Condensed Matter Physics Deep learning double-well Dynamics hybrid neural network Molecular Neural networks Optical and Plasma Physics Particle and Nuclear Physics Physics Physics and Astronomy Research Article Spectrum analysis

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    TN_cdi_proquest_journals_2574778415

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    https://collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2574778415

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