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We propose a general method to identify nonlinear Fokker--Planck--Kolmogorov equations (FPK equations) as gradient flows on the space of probability measures on $\mathbb{R}^d$ with a natural differential geometry. Our notion of gradient…

Analysis of PDEs · Mathematics 2024-11-11 Marco Rehmeier , Michael Röckner

A uniform dimensional result for normally reflected Brownian motion (RBM) in a large class of non-smooth domains is established. Exact Hausdorff dimensions for the boundary occupation time and the boundary trace of RBM are given. Extensions…

Probability · Mathematics 2007-05-23 Itai Benjamini , Zhen-Qing Chen , Steffen Rohde

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…

Optimization and Control · Mathematics 2020-06-16 Wuchen Li , Shu Liu , Hongyuan Zha , Haomin Zhou

We prove large deviations for $g(t)$-Brownian motion in a complete, evolving Riemannian manifold $M$ with respect to a collection $\{g(t)\}_{t\in [0,1]}$ of Riemannian metrics, smoothly depending on $t$. We show how the large deviations are…

Probability · Mathematics 2020-04-02 Rik Versendaal

We derive new gradient flows of divergence functions in the probability space embedded with a class of Riemannian metrics. The Riemannian metric tensor is built from the transported Hessian operator of an entropy function. The new gradient…

Information Theory · Computer Science 2019-05-15 Wuchen Li , Lexing Ying

The present work is devoted to the study of the large time behaviour of a critical Brownian diffusion in two dimensions, whose drift is divergence-free, ergodic and given by the curl of the 2-dimensional Gaussian Free Field. We prove the…

Probability · Mathematics 2022-11-04 Giuseppe Cannizzaro , Levi Haunschmid-Sibitz , Fabio Toninelli

We study nonlinear degenerate parabolic equations of Fokker-Planck type which can be viewed as gradient flows with respect to the recently introduced spherical Hellinger-Kantorovich distance. The driving entropy is not assumed to be…

Functional Analysis · Mathematics 2019-04-03 Stanislav Kondratyev , Dmitry Vorotnikov

We study the Wasserstein gradient flow of the Sinkhorn divergence when both the source and the target are Gaussian distributions. We prove the existence of a flow that stays in the class of Gaussian distributions, and is unique in the…

Analysis of PDEs · Mathematics 2026-02-20 Mathis Hardion , Théo Lacombe

We study the equation of one-dimensional quasistatic nonlinear viscoelasticity with Dirichlet boundary conditions, in the particular case that the underlying dissipation geometry (provided by the viscosity) is comparable to the Bhattacharya…

Analysis of PDEs · Mathematics 2026-05-12 Alexander Mielke , Billy Sumners

We study both the local and global existence of a gradient flow of the Sinai-Ruelle-Bowen entropy functional on a Hilbert manifold of expanding maps of a circle equipped with a Sobolev norm in the tangent space of the manifold. We show…

Mathematical Physics · Physics 2023-06-22 Miaohua Jiang

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…

Dynamical Systems · Mathematics 2017-09-26 Shui-Nee Chow , Wuchen Li , Haomin Zhou

We construct a stochastic model showing the relationship between noise, gradient flows and rate-independent systems. The model consists of a one-dimensional birth-death process on a lattice, with rates derived from Kramers' law as an…

Mathematical Physics · Physics 2015-09-30 Giovanni A. Bonaschi , Mark A. Peletier

The $W$-random graphs provide a flexible framework for modeling large random networks. Using the Large Deviation Principle (LDP) for $W$-random graphs from [9], we prove the LDP for the corresponding class of random symmetric…

Probability · Mathematics 2024-05-08 Mahya Ghandehari , Georgi S. Medvedev

The propagation of gradient flow structures from microscopic to macroscopic models is a topic of high current interest. In this paper we discuss this propagation in a model for the diffusion of particles interacting via hard-core exclusion…

Analysis of PDEs · Mathematics 2020-08-18 Maria Bruna , Martin Burger , José Antonio Carrillo

In the present paper, we prove that the Wasserstein distance on the space of continuous sample-paths equipped with the supremum norm between the laws of a uniformly elliptic one-dimensional diffusion process and its Euler discretization…

Probability · Mathematics 2014-04-29 A. Alfonsi , B. Jourdain , A. Kohatsu-Higa

We construct a family of semimartingales that describes the behavior of a particle system with sticky-reflecting interaction. The model is a physical improvement of the Howitt-Warren flow, an infinite system of diffusion particles on the…

Probability · Mathematics 2022-05-02 Vitalii Konarovskyi

We consider a diffusion equation in $\mathbb{R}^d$ with drift equal to the gradient of a homogeneous potential of degree $1+\gamma$, with $0<\gamma<1$, and local variance equal to $\varepsilon^2$ with $\varepsilon\to 0$. The associated…

Probability · Mathematics 2026-03-04 Paola Bermolen , Valeria Goicoechea , José R. León

We prove that reflected Brownian motion with normal reflections in a convex domain satisfies a dimension free Talagrand type transportation cost-information inequality. The result is generalized to other reflected diffusions with suitable…

Probability · Mathematics 2019-02-12 Soumik Pal , Andrey Sarantsev

We consider eigenvalues of generalized Wishart processes as well as particle systems, of which the empirical measures converge to deterministic measures as the dimension goes to infinity. In this paper, we obtain central limit theorems to…

Probability · Mathematics 2019-08-12 Jian Song , Jianfeng Yao , Wangjun Yuan

We study the Wasserstein metric $W_p$, a notion of distance between two probability distributions, from the perspective of Fourier Analysis and discuss applications. In particular, we bound the Earth Mover Distance $W_1$ between the…

Classical Analysis and ODEs · Mathematics 2020-09-15 Stefan Steinerberger