We consider finite-volume approximations of Fokker-Planck equations on bounded convex domains in R d and study the corresponding gradient flow structures. We reprove the convergence of the discrete to continuous Fokker-Planck equation via the method of evolutionary Γ - convergence, i.e., we pass to the limit at the level of the gradient flow structures, generalizing the one-dimensional result obtained by Disser and Liero. The proof is of variational nature and relies on a Mosco convergence result for functionals in the discrete-to-continuum limit that is of independent interest. Our results apply to arbitrary regular meshes, even though the associated discrete transport distances may fail to converge to the Wasserstein distance in this generality.

Evolutionary γ -convergence of entropic gradient flow structures for fokker-planck equations in multiple dimensions / D. Forkert, J. Maas, L. Portinale. - In: SIAM JOURNAL ON MATHEMATICAL ANALYSIS. - ISSN 0036-1410. - 54:4(2022), pp. 4297-4333. [10.1137/21M1410968]

Evolutionary γ -convergence of entropic gradient flow structures for fokker-planck equations in multiple dimensions

L. Portinale
Ultimo
2022

Abstract

We consider finite-volume approximations of Fokker-Planck equations on bounded convex domains in R d and study the corresponding gradient flow structures. We reprove the convergence of the discrete to continuous Fokker-Planck equation via the method of evolutionary Γ - convergence, i.e., we pass to the limit at the level of the gradient flow structures, generalizing the one-dimensional result obtained by Disser and Liero. The proof is of variational nature and relies on a Mosco convergence result for functionals in the discrete-to-continuum limit that is of independent interest. Our results apply to arbitrary regular meshes, even though the associated discrete transport distances may fail to converge to the Wasserstein distance in this generality.
evolutionary Γ -convergence; Fokker-Planck equation; gradient flow;
Settore MATH-03/A - Analisi matematica
   Optimal Transport and Stochastic Dynamics
   OPTRASTOCH
   European Commission
   Horizon 2020 Framework Programme
   716117
2022
18-lug-2022
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/1158801
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