Nonlinear rough Fokker-Planck equations

Fuente: arXiv
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Auteurs principaux: Bugini, Fabio, Friz, Peter K., Stannat, Wilhelm
Format: Preprint
Publié: 2025
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author Bugini, Fabio
Friz, Peter K.
Stannat, Wilhelm
author_facet Bugini, Fabio
Friz, Peter K.
Stannat, Wilhelm
contents McKean-Vlasov SDEs describe systems where the dynamics depend on the law of the process. The corresponding Fokker-Planck equation is a nonlinear, nonlocal PDE for the corresponding measure flow. In the presence of common noise and conditional law dependence, the evolution becomes random and is governed by a stochastic Fokker-Planck equation; that is, a nonlinear, nonlocal SPDE in the space of measures. (Such equations constitute an important ingredient in the theory of mean-field games with common noise.) Well-posedness of such SPDEs is a difficult problem, the best result to date due to Coghi-Gess (2019), which however comes with dimension-dependent regularity assumptions. In the present work, we show how rough path techniques can circumvent these entirely. Hence, and somewhat contrarily to common believe, the use of rough paths leads to substantially less regularity demands on the coefficients than methods rooted in classical stochastic analysis methods.
format Preprint
id arxiv_https___arxiv_org_abs_2507_17469
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Nonlinear rough Fokker-Planck equations
Bugini, Fabio
Friz, Peter K.
Stannat, Wilhelm
Probability
60L50, 35Q84
McKean-Vlasov SDEs describe systems where the dynamics depend on the law of the process. The corresponding Fokker-Planck equation is a nonlinear, nonlocal PDE for the corresponding measure flow. In the presence of common noise and conditional law dependence, the evolution becomes random and is governed by a stochastic Fokker-Planck equation; that is, a nonlinear, nonlocal SPDE in the space of measures. (Such equations constitute an important ingredient in the theory of mean-field games with common noise.) Well-posedness of such SPDEs is a difficult problem, the best result to date due to Coghi-Gess (2019), which however comes with dimension-dependent regularity assumptions. In the present work, we show how rough path techniques can circumvent these entirely. Hence, and somewhat contrarily to common believe, the use of rough paths leads to substantially less regularity demands on the coefficients than methods rooted in classical stochastic analysis methods.
title Nonlinear rough Fokker-Planck equations
topic Probability
60L50, 35Q84
url https://arxiv.org/abs/2507.17469