Quantitative particle approximation of nonlinear stochastic Fokker-Planck equations with singular kernel

Fuente: arXiv
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Main Authors: Knorst, Josué, Olivera, Christian, de Souza, Alexandre B.
Format: Preprint
Published: 2024
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author Knorst, Josué
Olivera, Christian
de Souza, Alexandre B.
author_facet Knorst, Josué
Olivera, Christian
de Souza, Alexandre B.
contents We derive quantitative estimates for large stochastic systems of interacting particles perturbed by both idiosyncratic and environmental noises, as well as singular kernels. We prove that the (mollified) empirical process converges to the solution of the nonlinear stochastic Fokker-Planck equation. The proof is based on Itô's formula for $H_{q}^{1}$-valued process, commutator estimates, and some estimations for the regularization of the empirical measure. Moreover, we show that the aforementioned equation admits a unique strong solution in the probabilistic sense. The approach applies to repulsive and attractive kernels.
format Preprint
id arxiv_https___arxiv_org_abs_2412_05950
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Quantitative particle approximation of nonlinear stochastic Fokker-Planck equations with singular kernel
Knorst, Josué
Olivera, Christian
de Souza, Alexandre B.
Probability
Analysis of PDEs
We derive quantitative estimates for large stochastic systems of interacting particles perturbed by both idiosyncratic and environmental noises, as well as singular kernels. We prove that the (mollified) empirical process converges to the solution of the nonlinear stochastic Fokker-Planck equation. The proof is based on Itô's formula for $H_{q}^{1}$-valued process, commutator estimates, and some estimations for the regularization of the empirical measure. Moreover, we show that the aforementioned equation admits a unique strong solution in the probabilistic sense. The approach applies to repulsive and attractive kernels.
title Quantitative particle approximation of nonlinear stochastic Fokker-Planck equations with singular kernel
topic Probability
Analysis of PDEs
url https://arxiv.org/abs/2412.05950