Orateur
Daniel Yaacoub
(CNRS, LAPLACE (UMR 5213))
Description
Recent advances have made it possible to develop path-space probabilistic representations of mesoscopic Boltzmann transport nonlinearly coupled to a self-consistent submodel of the force field through forward approaches based on continuous branching stochastic processes. In this work, path-space probabilistic representations of free-space Poisson–Vlasov and Poisson–Boltzmann systems are presented. This yields novel propagator representations and opens new avenues for efficient and benchmark simulations through the use of new Branching Backward Monte Carlo (BBMC) algorithms.