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Related papers: Kac's Program in Kinetic Theory

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This article is a continuation of our first work \cite{chaudruraynal:frikha}. We here establish some new quantitative estimates for propagation of chaos of non-linear stochastic differential equations in the sense of McKean-Vlasov. We…

Analysis of PDEs · Mathematics 2021-08-26 Noufel Frikha , Paul-Eric Chaudru de Raynal

We consider backward stochastic differential equations (BSDEs) with mean-field and McKean-Vlasov interactions in their generators in a general setting, where the drivers are square-integrable martingales, with a focus on the independent…

Probability · Mathematics 2024-08-27 Antonis Papapantoleon , Alexandros Saplaouras , Stefanos Theodorakopoulos

In this paper, we study propagation of chaos for the parabolic-parabolic Keller-Segel model with a logarithmic cut-off by establishing a rigorous convergence analysis from a stochastic particle system to the parabolic-parabolic Keller-Segel…

Analysis of PDEs · Mathematics 2022-09-07 Li Chen , Shu Wang , Rong Yang

This article examines the relationship between classical and quantum propagation of chaos. (In this context, "chaos" refers to the Boltzmann's Ansatz of molecular disorder, not to chaotic dynamics.) Classical propagation of chaos is shown…

Quantum Physics · Physics 2007-05-23 Alex D Gottlieb

Systems of stochastic particles evolving in a multi-well energy landscape and attracted to their barycenter is the prototypical example of mean-field process undergoing phase transitions: at low temperature, the corresponding mean-field…

Probability · Mathematics 2025-03-04 Pierre Monmarché

We consider Kac's 1D N-particle system coupled to an ideal thermostat at temperature T, introduced by Bonetto, Loss, and Vaidyanathan in 2014. We obtain a propagation of chaos result for this system, with explicit and uniform-in-time rates…

Probability · Mathematics 2021-05-19 Roberto Cortez , Hagop Tossounian

We study a stochastic system of $N$ interacting particles which models bimolecular chemical reaction-diffusion. In this model, each particle $i$ carries two attributes: the spatial location $X_t^i\in \mathbb{T}^d$, and the type $\Xi_t^i\in…

Analysis of PDEs · Mathematics 2020-01-24 Tau Shean Lim , Yulong Lu , James Nolen

We develop a mean-field theory for large, non-exchangeable particle (agent) systems where the states and interaction weights co-evolve in a coupled system of SDEs. A first main result is the establishment of the propagation of…

Probability · Mathematics 2025-12-30 Datong Zhou

We consider a system of $N$ interacting particles, described by SDEs driven by Poisson random measures, where the coefficients depend on the empirical measure of the system. Every particle jumps with a jump rate depending on its position.…

Probability · Mathematics 2025-02-19 Eva Löcherbach , Dasha Loukianova , Elisa Marini

We discuss old and new results on the mathematical justification of Boltzmann's equation. The classical result along these lines is a theorem which was proven by Lanford in the 1970s. This paper is naturally divided into three parts. I.…

Analysis of PDEs · Mathematics 2018-07-02 Ryan Denlinger

The Bird and Nanbu systems are particle systems used to approximate the solution of the mollied Boltzmann equation. In particular, they have the propagation of chaos property. Following [GM94, GM97, GM99], we use coupling techniques and…

Probability · Mathematics 2016-10-19 Sylvain Rubenthaler

Combining the results of [14] and [10], the trend to equilibrium in large time is studied for a large particle system associated to a Vlasov-Fokker-Planck equation. Under some conditions (that allow non-convex confining potentials) the…

Probability · Mathematics 2021-11-17 Arnaud Guillin , Pierre Monmarché

A Langevin equation is suggested to describe a system driven by correlated Gaussian white noise as well as with positive and negative damping demarcated by a critical velocity. The equation can be transformed into the Fokker-Planck equation…

Physics and Society · Physics 2019-09-11 Peng Wang , Feng-Chun Pan , Jie Huo , Xu-Ming Wang

Mark Kac introduced what is now called 'the Kac Walk' with the aim of investigating the spatially homogeneous Boltzmann equation by probabilistic means. Much recent work, discussed below, on Kac's program has run in the other direction:…

Mathematical Physics · Physics 2017-04-18 Eric A. Carlen , Maria C. Carvalho , Amit Einav

The trend to equilibrium in large time is studied for a large particle system associated to a Vlasov-Fokker-Planck equation in the presence of a convex external potential, without smallness restriction on the interaction. From this are…

Probability · Mathematics 2017-09-11 Pierre Monmarché

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

Motivated by several applications, including neuronal models, we consider the McKean-Vlasov limit for mean-field systems of interacting diffusions with simultaneous jumps. We prove propagation of chaos via a coupling technique that involves…

Probability · Mathematics 2017-04-05 Luisa Andreis , Paolo Dai Pra , Markus Fischer

A criterion for proving a strong form of propagation of chaos on the path space, known as entropy chaos, for a general interacting diffusion system is proposed. Our analysis focuses on the class of conservative diffusions introduced by…

Probability · Mathematics 2026-04-17 Luigi Borasi , Francesco Carlo De Vecchi , Stefania Ugolini

In this paper, we first investigate the well-posedness of a backward stochastic differential equation where the driver depends on the law of the solution conditioned to a common noise. Under standard assumptions, we show that existence and…

Probability · Mathematics 2022-09-29 Remi Moreau

We study the rate of propagation of chaos for a McKean--Vlasov equation with conditional expectation terms in the drift. We use a (regularized) Nadaraya--Watson estimator at a particle level to approximate the conditional expectations; we…

Probability · Mathematics 2025-07-31 Manuel Arnese