Elucidating the Conformal Structure of the Brinkman Penalisation Method for Geometry-Adapted, Structure-Preserving Operator Learning of Hamiltonian PDEs
ScientificML
This paper reveals the multi-conformal symplectic structure preserved by Hamiltonian PDEs regularized via Brinkman penalization, proving an exact local conservation law under a compatibility condition linking the symplectic matrix and penalization projection.
New See LICENSE file Hamiltonian PDEsOperator LearningStructure-Preserving