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physics.comp-ph2026
Stochastic Physics-Constrained Operator Inference for Complex Systems
Changhong Mou
Quadratically nonlinear systems driven by additive noise arise throughout science and engineering, both as stochastic dynamical systems in their own right and as reduced-order mode…
physics.comp-ph2026
ATLAS-NN: Adaptive Transfer Learnable Symplectic-aware Neural Network for Long-Time Hamiltonian Dynamics
Changhong Mou, Dinghua Xu, Xiyue Zuo +2
Modeling Hamiltonian systems over long temporal intervals remains a significant challenge due to intrinsic multiscale structures and rapid nonlinear transitions. While Hamiltonian…
physics.comp-ph2025
PAS-Net: Physics-informed Adaptive Scale Deep Operator Network
Changhong Mou, Yeyu Zhang, Xuewen Zhu +1
Nonlinear physical phenomena often show complex multiscale interactions; motivated by the principles of multiscale modeling in scientific computing, we propose PAS-Net, a physics-i…