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math.NA2025
Structure-Preserving Transfer of Grad-Shafranov Equilibria to Magnetohydrodynamic Solvers
Rushan Zhang, Golo Wimmer, Qi Tang
Magnetohydrodynamic (MHD) solvers used to study dynamic plasmas for magnetic confinement fusion typically rely on initial conditions that describe force balance, which are provided…
math.NA2025
Reduced-order modeling of Hamiltonian dynamics based on symplectic neural networks
Yongsheng Chen, Wei Guo, Qi Tang +1
We introduce a novel data-driven symplectic induced-order modeling (ROM) framework for high-dimensional Hamiltonian systems that unifies latent-space discovery and dynamics learnin…
math.NA2025★ 1 cited
Structure-Preserving Neural Ordinary Differential Equations for Stiff Systems
Allen Alvarez Loya, Daniel A. Serino, J. W. Burby +1
Neural ordinary differential equations (NODEs) are an effective approach for data-driven modeling of dynamical systems arising from simulations and experiments. One of the major sh…