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math.NA2026
A multi-physics structure-preserving integrator with uniform error bounds for relativistic charged-particle dynamics under strong magnetic fields
Mengting Hu, Yifa Tang, Bin Wang
In this paper, we develop an explicit multi-physics structure-preserving Strang splitting scheme for a four-dimensional relativistic charged-particle dynamical system in the presen…
cs.LG2026
CSympNet-ID: conformal-symplectic map learning for linearly damped Hamiltonian systems
Jiale Gong, Pengzhan Jin, Dongyang Kuang +2
Learning dissipative dynamics from discrete observations is essential for reliable long-horizon prediction and physically meaningful parameter identification. For linearly damped H…
cs.LG2026
Learning symplectic model reduction based on an approximation theorem of symplectic embeddings
Liyi Feng, Yifa Tang, Yulin Xie +2
High-dimensional Hamiltonian systems play a central role in many scientific and engineering disciplines, with dynamics that evolve on symplectic manifolds. Although deep learning p…