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math.NA2026

Hermite Semi-Lagrangian schemes on triangular meshes for advection equations

Ali Elarif, Michel Mehrenberger, Laurent Navoret

High-order Hermite semi-Lagrangian schemes on unstructured triangular grids are proposed for advection equations, based on Bell and Argyris finite elements. Nodal semi-Lagrangian s…

math.NA2025

Neural semi-Lagrangian method for high-dimensional advection-diffusion problems

Emmanuel Franck, Victor Michel-Dansac, Laurent Navoret +1

This work is devoted to the numerical approximation of high-dimensional advection-diffusion equations. It is well-known that classical methods, such as the finite volume method, su…

math.NA2025

Reduced Particle in Cell method for the Vlasov-Poisson system using auto-encoder and Hamiltonian neural

Emmanuel Franck, Laurent Navoret, Vincent Vigon +2

Hamiltonian particle-based simulations of plasma dynamics are inherently computationally intensive, primarily due to the large number of particles required to obtain accurate solut…

math.NA2024

Hamiltonian reduction using a convolutional auto-encoder coupled to an Hamiltonian neural network

Raphaël Côte, Emmanuel Franck, Laurent Navoret +2

The reduction of Hamiltonian systems aims to build smaller reduced models, valid over a certain range of time and parameters, in order to reduce computing time. By maintaining the…

math.NA2024

Fourth-order entropy-stable lattice Boltzmann schemes for hyperbolic systems

Thomas Bellotti, Philippe Helluy, Laurent Navoret

We present a novel framework for the development of fourth-order lattice Boltzmann schemes to tackle multidimensional nonlinear systems of conservation laws. As for other numerical…

math.NA2024

Approximately well-balanced Discontinuous Galerkin methods using bases enriched with Physics-Informed Neural Networks

Emmanuel Franck, Victor Michel-Dansac, Laurent Navoret

This work concerns the enrichment of Discontinuous Galerkin (DG) bases, so that the resulting scheme provides a much better approximation of steady solutions to hyperbolic systems…