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Jonathan Colen1,2,3, Alexis Poncet4, Denis Bartolo4

  • 1James Franck Institute, <a href="https://ror.org/024mw5h28">University of Chicago</a>, Chicago, Illinois 60637, USA.

Physical review letters
|September 20, 2024
PubMed
概括

我们开发了一个数据驱动的管道,将机器学习和物理结合起来,在微流体实验中建模非线性动力学. 这种方法揭示了非互惠的水力动力学相互作用如何稳定和促进滴水晶体中的非线性波传播.

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