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We establish sharp rates for propagation of chaos in R\'enyi divergences for interacting diffusion systems at stationarity. Building upon the entropic hierarchy established in Lacker (2023), we show that under strong isoperimetry and weak…

Probability · Mathematics 2026-02-10 Matthew S. Zhang

New quantitative propagation of chaos results for mean field diffusion are proved via local and global entropy estimates. In the first result we work on the torus and consider singular, divergence free interactions $K\in L^p$, $p>d$. We…

Probability · Mathematics 2023-08-02 Yi Han

This paper develops a non-asymptotic, local approach to quantitative propagation of chaos for a wide class of mean field diffusive dynamics. For a system of $n$ interacting particles, the relative entropy between the marginal law of $k$…

Probability · Mathematics 2023-05-31 Daniel Lacker

We derive quantitative estimates proving the propagation of chaos for large stochastic systems of interacting particles. We obtain explicit bounds on the relative entropy between the joint law of the particles and the tensorized law at the…

Analysis of PDEs · Mathematics 2018-10-17 Pierre-Emmanuel Jabin , Zhenfu Wang

In this paper, we study diffusions with bounded pairwise interaction. We show for the first time propagation of chaos on arbitrary time horizons in a stronger $L^2$-based distance, as opposed to the usual Wasserstein or relative entropy…

Probability · Mathematics 2025-03-12 Elias Hess-Childs , Keefer Rowan

We study the long time behavior of second order particle systems interacting through global Lipschitz kernels. Combining hypocoercivity method in [37] and relative entropy method in [25], we are able to overcome the degeneracy of diffusion…

Analysis of PDEs · Mathematics 2024-09-05 Yun Gong , Zhenfu Wang , Pengzhi Xie

We present a method to obtain sharp local propagation of chaos results for a system of N particles with a diffusion coefficient that it not constant and may depend of the empirical measure. This extends the recent works of Lacker [14] and…

Probability · Mathematics 2024-10-29 Jules Grass , Arnaud Guillin , Christophe Poquet

We consider particle systems that evolve by inertialess binary interaction through general non-attractive kernels of singularity $|x|^{-\alpha}$ with $\alpha<d-1$. We prove a quantitative mean-field limit in terms of Wasserstein distances…

Analysis of PDEs · Mathematics 2025-09-18 Richard M. Höfer , Richard Schubert

We present a new method for proving sharp local propagation of chaos in Fisher Information for particles with smooth interaction and drift. We rely on a new Lemma computing the Fisher Information of two diffusion processes with smooth…

Probability · Mathematics 2025-11-26 Jules Grass , Christophe Poquet , Arnaud Guillin

We consider a stochastic system of $N$ particles, usually called vortices in that setting, approximating the 2D Navier-Stokes equation written in vorticity. Assuming that the initial distribution of the position and circulation of the…

Analysis of PDEs · Mathematics 2016-03-16 Nicolas Fournier , Maxime Hauray , Stéphane Mischler

In this work we deal with the local in time propagation of chaos without cut-off for some two dimensional fractional Keller Segel equations. More precisely the diffusion considered here is given by the fractional Laplacian operator…

Analysis of PDEs · Mathematics 2018-07-12 Samir Salem

We develop a new technique for establishing quantitative propagation of chaos for systems of interacting particles. Using this technique we prove propagation of chaos for diffusing particles whose interaction kernel is merely H\"older…

Analysis of PDEs · Mathematics 2016-12-09 Thomas Holding

In this paper, uniform in time quantitative propagation of chaos in $L^1$-Wasserstein distance for mean field interacting particle system is derived, where the diffusion coefficient is allowed to be interacting and the drift is assumed to…

Probability · Mathematics 2025-10-29 Xing Huang

We prove the optimal rate of quantitative propagation of chaos, uniformly in time, for interacting diffusions. Our main examples are interactions governed by convex potentials and models on the torus with small interactions. We show that…

Probability · Mathematics 2023-01-23 Daniel Lacker , Luc Le Flem

We derive the quantitative estimates of propagation of chaos for the large interacting particle systems in terms of the relative entropy between the joint law of the particles and the tensorized law of the mean field PDE. We resolve this…

Analysis of PDEs · Mathematics 2025-09-16 Xuanrui Feng , Zhenfu Wang

We consider the 3D Landau equation for moderately soft potentials ($\gamma\in(-2,0)$ with the usual notation) as well as a stochastic system of $N$ particles approximating it. We first establish some strong/weak stability estimates for the…

Probability · Mathematics 2015-01-09 Nicolas Fournier , Maxime Hauray

We prove propagation of chaos at explicit polynomial rates in Wasserstein distance W_2 for Kac's N-particle system associated with the spatially homogeneous Boltzmann equation for Maxwell molecules, with and without cutoff. Our approach is…

Mathematical Physics · Physics 2017-12-27 Roberto Cortez , Joaquin Fontbona

For any weakly interacting particle system with bounded kernel, we give uniform-in-time estimates of the $L^2$ norm of correlation functions, provided that the diffusion coefficient is large enough. When the condition on the kernels is more…

Analysis of PDEs · Mathematics 2024-11-26 Pengzhi Xie

We study a nonlocal adhesion model for two interacting tumor cell phenotypes, combining diffusion, pairwise interactions, and random phenotypic switching. The system admits a microscopic diffusion--jump particle description whose mean-field…

Analysis of PDEs · Mathematics 2026-03-16 Myeongju Chae , Young-Pil Choi

We prove the quantitative propagation of chaos for stochastic particle systems with interaction in both the drift and the diffusion coefficients, provided the drift kernel is bounded and free of Lipschitz or smoothness assumptions. Our…

Analysis of PDEs · Mathematics 2026-04-14 Ning Jiang , Rongli Mo
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