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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

In this work, we prove the well-posedness and propagation of chaos for a stochastic particle system in mean-field interaction under the assumption that the interacting kernel belongs to a suitable $L_t^q-L_x^p$ space. Contrary to the large…

Probability · Mathematics 2023-07-19 Milica Tomašević

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

A new class of particle systems with sequential interaction is proposed to approximate the McKean-Vlasov process that originally arises as the limit of the mean-field interacting particle system. The weighted empirical measure of this…

Probability · Mathematics 2023-01-25 Kai Du , Yifan Jiang , Xiaochen Li

We introduce a framework to prove propagation of chaos for interacting particle systems with singular, density-dependent interactions, a classical challenge in mean-field theory. Our approach is to define the dynamics implicitly via a…

Analysis of PDEs · Mathematics 2025-07-22 Qian Qi

This work addresses the propagation of chaos properties in a class of moderately interacting particle systems for the approximation of singular kinetic McKean-Vlasov SDEs driven by alpha-stable processes.

Analysis of PDEs · Mathematics 2026-02-16 Zimo Hao , Jean-Francois Jabir , Stéphane Menozzi , Michael Röckner , Xicheng Zhang

The notion of propagation of chaos for large systems of interacting particles originates in statistical physics and has recently become a central notion in many areas of applied mathematics. The present review describes old and new methods…

Probability · Mathematics 2023-02-15 Louis-Pierre Chaintron , Antoine Diez

The notion of propagation of chaos for large systems of interacting particles originates in statistical physics and has recently become a central notion in many areas of applied mathematics. The present review describes old and new methods…

Probability · Mathematics 2023-02-15 Louis-Pierre Chaintron , Antoine Diez

The propagation of chaos is a central concept of kinetic theory that serves to relate the equations of Boltzmann and Vlasov to the dynamics of many-particle systems. Propagation of chaos means that molecular chaos, i.e., the stochastic…

Probability · Mathematics 2007-05-23 Alexander David Gottlieb

A system of interacting particles described by stochastic differential equations is considered. As oppopsed to the usual model, where the noise perturbations acting on different particles are independent, here the particles are subject to…

Analysis of PDEs · Mathematics 2016-06-23 Michele Coghi , Franco Flandoli

This paper develops a theory of propagation of chaos for a system of weakly interacting particles whose terminal configuration is fixed as opposed to the initial configuration as customary. Such systems are modeled by backward stochastic…

Probability · Mathematics 2019-11-19 Mathieu Laurière , Ludovic Tangpi

The aim of this note is to revisit propagation of chaos for a Langevin-type interacting particle system used for sampling probability measures. The interacting particle system we consider coincides, in the setting of a log-quadratic target…

Probability · Mathematics 2024-09-11 U Vaes

Propagation of chaos for interacting particle systems has been an active research topic over decades. We propose an alternative approach to study the mean-field limit of the stochastic interacting particle systems via tools from information…

Probability · Mathematics 2025-01-07 Lei Li , Yuelin Wang , Yuliang Wang

We consider interacting systems particle driven by i.i.d. fractional Brownian motions, subject to irregular, possibly distributional, pairwise interactions. We show propagation of chaos and mean field convergence to the law of the…

Probability · Mathematics 2025-12-02 Lucio Galeati , Khoa Lê , Avi Mayorcas

In this paper, quantitative propagation of chaos in $L^\eta$($\eta\in(0,1]$)-Wasserstein distance for mean field interacting particle system is derived, where the diffusion coefficient is allowed to be interacting and the initial…

Probability · Mathematics 2024-08-30 Xing Huang

In this work we show the strong convergence of propagation of chaos for the particle approximation of McKean-Vlasov SDEs with singular $L^p$-interactions as well as for the moderate interaction particle systems on the level of particle…

Probability · Mathematics 2022-06-17 Zimo Hao , Michael Röckner , Xicheng Zhang

Based on a coupling approach, we prove uniform in time propagation of chaos for weakly interacting mean-field particle systems with possibly non-convex confinement and interaction potentials. The approach is based on a combination of…

Probability · Mathematics 2018-05-30 Alain Durmus , Andreas Eberle , Arnaud Guillin , Raphael Zimmer

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

This paper is devoted to the study of mean-field limit for systems of indistinguables particles undergoing collision processes. As formulated by Kac \cite{Kac1956} this limit is based on the {\em chaos propagation}, and we (1) prove and…

Analysis of PDEs · Mathematics 2010-01-19 Stéphane Mischler , Clément Mouhot

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
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