What’s Next? Predicting Hamiltonian Dynamics from Discrete Observations of a Vector Field

Database and Expert Systems Applications(2022)

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摘要
We present several methods for predicting the dynamics of Hamiltonian systems from discrete observation of their vector field. Each method is either informed or uninformed of the Hamiltonian property. We empirically and comparatively evaluate the methods and observe that information that the system is Hamiltonian can be effectively informed, and that different methods strike different trade-offs between efficiency and effectiveness for different dynamical systems.
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关键词
Trajectory prediction, Physics-informed neural network, Data analysis, Inductive bias, Learning bias
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