Symplectic Neural Flows for Modeling and Discovery

ArXi:2412.16787v2 Announce Type: replace Hamilton's equations are fundamental for modeling complex physical systems, where preserving key properties such as energy and momentum is crucial for reliable long-term simulations. Geometric integrators are widely used for this purpose, but neural network-based methods that incorporate these principles remain underexplored. This work