Port-Hamiltonian neural networks extended to PDEs recover the Hamiltonian and dissipation of nonlinear string dynamics from data and outperform non-physics-informed baselines.
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New energetic spectral-element time integrators for phase-field gradient systems that preserve discrete energy dissipation and mass conservation, with numerical tests showing better performance than BDF4 and ETDRK4 on Allen-Cahn problems.
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Identifying the nonlinear string dynamics with port-Hamiltonian neural networks
Port-Hamiltonian neural networks extended to PDEs recover the Hamiltonian and dissipation of nonlinear string dynamics from data and outperform non-physics-informed baselines.
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Energetic Spectral-Element Time Marching Methods for Phase-Field Nonlinear Gradient Systems
New energetic spectral-element time integrators for phase-field gradient systems that preserve discrete energy dissipation and mass conservation, with numerical tests showing better performance than BDF4 and ETDRK4 on Allen-Cahn problems.