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We introduce a stochastic particle system that corresponds to the Fokker-Planck equation with decay in the many-particles limit, and study its large deviations. We show that the large-deviation rate functional corresponds to an…

偏微分方程分析 · 数学 2013-03-08 Mark Peletier , Michiel Renger , Marco Veneroni

We consider a Fokker-Planck equation which is coupled to an externally given time-dependent constraint on its first moment. This constraint introduces a Lagrange-multiplier which renders the equation nonlocal and nonlinear. In this paper we…

偏微分方程分析 · 数学 2018-11-28 Simon Eberle , Barbara Niethammer , André Schlichting

In this work, we investigate a variational formulation for a time-fractional Fokker-Planck equation which arises in the study of complex physical systems involving anomalously slow diffusion. The model involves a fractional-order Caputo…

数值分析 · 数学 2020-06-05 Manh Hong Duong , Bangti Jin

We prove the convergence of a Wasserstein gradient flow of a free energy in inhomogeneous media. Both the energy and media can depend on the spatial variable in a fast oscillatory manner. In particular, we show that the gradient-flow…

偏微分方程分析 · 数学 2025-08-19 Yuan Gao , Nung Kwan Yip

Wasserstein gradient flows provide a powerful means of understanding and solving many diffusion equations. Specifically, Fokker-Planck equations, which model the diffusion of probability measures, can be understood as gradient descent over…

机器学习 · 计算机科学 2021-10-26 Petr Mokrov , Alexander Korotin , Lingxiao Li , Aude Genevay , Justin Solomon , Evgeny Burnaev

In this paper we identify the Fokker-Planck equation for (reflected) Sticky Brownian Motion as a Wasserstein gradient flow in the space of probability measures. The driving functional is the relative entropy with respect to a non-standard…

偏微分方程分析 · 数学 2025-01-27 Jean-Baptiste Casteras , Léonard Monsaingeon , Filippo Santambrogio

We study the large deviation rate functional for the empirical distribution of independent Brownian particles with drift. In one dimension, it has been shown by Adams, Dirr, Peletier and Zimmer that this functional is asymptotically…

概率论 · 数学 2016-01-11 Matthias Erbar , Jan Maas , Michiel Renger

We derive the Fokker-Planck equation on the parametric space. It is the Wasserstein gradient flow of relative entropy on the statistical manifold. We pull back the PDE to a finite dimensional ODE on parameter space. Some analytical example…

最优化与控制 · 数学 2020-06-16 Wuchen Li , Shu Liu , Hongyuan Zha , Haomin Zhou

The Fokker-Planck equation is one of the fundamental equations in nonequilibrium statistical mechanics, and this equation is known to be derived from the Wasserstein gradient flow equation with a free energy. This gradient flow equation…

数学物理 · 物理学 2024-08-08 Shin-itiro Goto

We consider a class of time-homogeneous diffusion processes on $\mathbb{R}^{n}$ with common invariant measure but varying volatility matrices. In Euclidean space, we show via stochastic control of the diffusion coefficient that the…

概率论 · 数学 2023-10-31 Bertram Tschiderer

In this paper, we study the Wasserstein gradient flow structure of the porous medium equation. We prove that, for the case of $q$-Gaussians on the real line, the functional derived by the JKO-discretization scheme is asymptotically…

偏微分方程分析 · 数学 2013-07-22 Manh Hong Duong

We describe conditions on non-gradient drift diffusion Fokker-Planck equations for its solutions to converge to equilibrium with a uniform exponential rate in Wasserstein distance. This asymptotic behaviour is related to a functional…

概率论 · 数学 2012-09-19 François Bolley , Ivan Gentil , Arnaud Guillin

We study the connection between a system of many independent Brownian particles on one hand and the deterministic diffusion equation on the other. For a fixed time step $h>0$, a large-deviations rate functional $J_h$ characterizes the…

概率论 · 数学 2015-05-18 Stefan Adams , Nicolas Dirr , Mark Peletier , Johannes Zimmer

We study a singular-limit problem arising in the modelling of chemical reactions. At finite {\epsilon} > 0, the system is described by a Fokker-Planck convection-diffusion equation with a double-well convection potential. This potential is…

偏微分方程分析 · 数学 2014-09-16 Steffen Arnrich , Alexander Mielke , Mark A. Peletier , Giuseppe Savaré , Marco Veneroni

We propose a new semi-discretization scheme to approximate nonlinear Fokker-Planck equations, by exploiting the gradient flow structures with respect to the 2-Wasserstein metric. We discretize the underlying state by a finite graph and…

数值分析 · 数学 2017-12-20 Shui-Nee Chow , Luca Dieci , Wuchen Li , Haomin Zhou

We study the Wasserstein gradient flow of semi-discrete energies in the space of probability measures, that is functionals depending on two measures-one being an absolutely continuous density and the other an atomic measure. These energies…

偏微分方程分析 · 数学 2026-03-05 Joao Miguel Machado

We study the emergence of gradient flows in Wasserstein distance as high friction limits of an abstract Euler flow generated by an energy functional. We develop a relative energy calculation that connects the Euler flow to the gradient flow…

偏微分方程分析 · 数学 2021-03-22 Corrado Lattanzio , Athanasios E. Tzavaras

We introduce a time discretization for Wasserstein gradient flows based on the classical Backward Differentiation Formula of order two. The main building block of the scheme is the notion of geodesic extrapolation in the Wasserstein space,…

偏微分方程分析 · 数学 2023-11-20 Thomas Gallouët , Andrea Natale , Gabriele Todeschi

We propose a variational finite volume scheme to approximate the solutions to Wasserstein gradient flows. The time discretization is based on an implicit linearization of the Wasserstein distance expressed thanks to Benamou-Brenier formula,…

数值分析 · 数学 2019-07-22 Clément Cancès , Thomas O. Gallouët , Gabriele Todeschi

We study the nonlinear Fokker-Planck equation on graphs, which is the gradient flow in the space of probability measures supported on the nodes with respect to the discrete Wasserstein metric. The energy functional driving the gradient flow…

动力系统 · 数学 2017-09-26 Shui-Nee Chow , Wuchen Li , Haomin Zhou
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