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Consider the metric space $(\mathcal{P}_2(\mathbb{R}^d),W_2)$ of square integrable laws on $\mathbb{R}^d$ with the topology induced by the 2-Wasserstein distance $W_2$. Let $\Phi: \mathcal{P}_2( \mathbb{R}^d) \to \mathbb{R}$ be a function…

Probability · Mathematics 2022-06-02 Jean-François Chassagneux , Lukasz Szpruch , Alvin Tse

Propagation of initially localized perturbations is investigated in chaotic coupled map lattices with long-range couplings decaying as a power of the distance. The initial perturbation propagates exponentially fast along the lattice, with a…

chao-dyn · Physics 2009-10-28 Alessandro Torcini , Stefano Lepri

This article investigates the propagation of chaos property for weakly interacting mild solutions to semilinear stochastic partial differential equations whose coefficients might not satisfy Lipschitz conditions. Furthermore, we derive…

Probability · Mathematics 2023-07-05 David Criens

A reorganized perturbation expansion with a propagator of soft infrared behavior is used to study the critical behavior of the mass gap. The condition of relativistic covariance fixes the form of the soft propagator. Finite approximants to…

High Energy Physics - Theory · Physics 2009-10-22 Peter Suranyi

We consider a system of $N$ Brownian particles, with or without inertia, interacting in the mean-field regime via a weak, smooth, long-range potential, and starting initially from an arbitrary exchangeable $N$-particle distribution. In this…

Probability · Mathematics 2025-05-13 Armand Bernou , Mitia Duerinckx , Matthieu Ménard

In this Letter we show that the analysis of Lyapunov-exponents fluctuations contributes to deepen our understanding of high-dimensional chaos. This is achieved by introducing a Gaussian approximation for the large deviation function that…

Chaotic Dynamics · Physics 2012-03-28 Pavel V. Kuptsov , Antonio Politi

Spatially structured neural networks driven by jump diffusion noise with monotone coefficients, fully path dependent delay and with a disorder parameter are considered. Well-posedness for the associated McKean-Vlasov equation and a…

Probability · Mathematics 2020-02-28 Sima Mehri , Michael Scheutzow , Wilhelm Stannat , Bijan Z. Zangeneh

We develop a limit theory for controlled path-dependent mean field stochastic partial differential equations (SPDEs) within the semigroup approach of Da Prato and Zabczyk. More precisely, we prove existence results for mean field limits and…

Probability · Mathematics 2026-05-20 David Criens , Moritz Ritter

The chaotic scattering theory is here extended to obtain escape-rate expressions for the transport coefficients appropriate for a simple classical fluid, or for a chemically reacting system. This theory allows various transport coefficients…

chao-dyn · Physics 2009-10-22 J. R. Dorfman , P. Gaspard

In this paper, we provide a general framework for investigating McKean-Vlasov stochastic partial differential equations. We first show the existence of weak solutions by combining the localizing approximation, Faedo-Galerkin technique,…

Probability · Mathematics 2025-08-12 Wei Hong , Shihu Li , Wei Liu

In this paper, we study the existence and pathwise uniqueness of strong solutions for jump-type McKean-Vlasov SDEs with irregular coefficients but uniform linear growth assumption. Moreover, the propagation of chaos and the convergence rate…

Probability · Mathematics 2024-02-12 Zhen Wang , Jie Ren , Yu Miao

Dynamical systems of N particles in \R^{D} interacting by a singular pair potential of mean field type are considered. The systems are assumed to be of gradient type and the existence of a macroscopic limit in the many particle limit is…

Mathematical Physics · Physics 2016-10-17 Robert J. Berman , Magnus Önnheim

We present a purely probabilistic proof of propagation of molecular chaos for $N$-particle systems in dimension $3$ with interaction forces scaling like $1/\vert q\vert^{\lambda}$ with $\lambda<2$ and cut-off at $q = N^{-1/3}$. The proof…

Mathematical Physics · Physics 2015-09-07 Niklas Boers , Peter Pickl

We develop a convergent variational perturbation theory for conditional probability densities of Markov processes. The power of the theory is illustrated by applying it to the diffusion of a particle in an anharmonic potential.

Condensed Matter · Physics 2009-11-07 Hagen Kleinert , Axel Pelster , Mihai V. Putz

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

The impact of quenched disorder on deterministic diffusion in chaotic dynamical systems is studied. As a simple example, we consider piecewise linear maps on the line. In computer simulations we find a complicated scenario of multiple…

Chaotic Dynamics · Physics 2009-11-07 R. Klages

In this paper we prove a large deviation principle (LDP) for the empirical measure of a general system of mean-field interacting diffusions with singular drift (as the number of particles tends to infinity) and show convergence to the…

Probability · Mathematics 2020-07-02 Jasper Hoeksema , Thomas Holding , Mario Maurelli , Oliver Tse

We consider weakly interacting diffusions on time varying random graphs. The system consists of a large number of nodes in which the state of each node is governed by a diffusion process that is influenced by the neighboring nodes. The…

Probability · Mathematics 2017-02-16 Shankar Bhamidi , Amarjit Budhiraja , Ruoyu Wu

A strong analogy is found between the evolution of localized disturbances in extended chaotic systems and the propagation of fronts separating different phases. A condition for the evolution to be controlled by nonlinear mechanisms is…

chao-dyn · Physics 2009-10-28 A. Torcini , P. Grassberger , A. Politi

We consider a system of classical Brownian particles interacting via a smooth long-range potential in the mean-field regime, and we analyze the propagation of chaos in form of sharp, uniform-in-time estimates on many-particle correlation…

Analysis of PDEs · Mathematics 2025-02-18 Armand Bernou , Mitia Duerinckx