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This paper considers an $n$-particle jump-diffusion system with mean filed interaction, where the coefficients are locally Lipschitz continuous. We address the convergence as $n\to\infty$ of the empirical measure of the jump-diffusions to…

Probability · Mathematics 2024-02-27 Zeqian Li

Many science phenomena are described as interacting particle systems (IPS). The mean field limit (MFL) of large all-to-all coupled deterministic IPS is given by the solution of a PDE, the Vlasov Equation (VE). Yet, many applications demand…

Analysis of PDEs · Mathematics 2021-12-21 Christian Kuehn , Chuang Xu

We establish a hydrodynamical limit for the averaging process on the complete graph with N vertices, showing that, after a timescale of order N, the empirical distribution of opinions converges to a unique measure. Moreover, if the initial…

Probability · Mathematics 2025-03-26 Alberto M. Campos , Tertuliano Franco , Markus Heydenreich , Marcel Schrocke

We consider a system of $N$ particles interacting through their empirical distribution on a finite state space in continuous time. In the formal limit as $N\to\infty$, the system takes the form of a nonlinear (McKean--Vlasov) Markov chain.…

Probability · Mathematics 2025-11-13 Asaf Cohen , Ethan Huffman

This paper establishes an indirect approximation theorem for the most probable transition pathway of a stochastic interacting particle system in the mean-field framework. This paper studied the problem of indirect approximation of the most…

Dynamical Systems · Mathematics 2026-05-27 Jianyu Chen , Ting Gao , Galina Strelkova , Jinqiao Duan

We consider a class of weakly interacting particle systems of mean-field type. The interactions between the particles are encoded in a graph sequence, i.e., two particles are interacting if and only if they are connected in the underlying…

Probability · Mathematics 2023-07-06 Gianmarco Bet , Fabio Coppini , Francesca R. Nardi

We consider a finite-state, continuous-time Markov process, represented in the "linear framework" by a directed graph with labelled edges which specifies the infinitesimal generator of the process. If the graph is strongly connected, the…

Biological Physics · Physics 2023-10-17 Ugur Cetiner , Jeremy Gunawardena

We prove limit theorems for systems of interacting diffusions on sparse graphs. For example, we deduce a hydrodynamic limit and the propagation of chaos property for the stochastic Kuramoto model with interactions determined by…

Probability · Mathematics 2020-01-01 Roberto I. Oliveira , Guilherme H. Reis , Lucas M. Stolerman

This paper deals with the derivation of the mean-field limit for multi-agent systems on a large class of sparse graphs. More specifically, the case of non-exchangeable multi-agent systems consisting of non-identical agents is addressed. The…

Probability · Mathematics 2025-11-21 Pierre-Emmanuel Jabin , David Poyato , Juan Soler

We investigate the mean-field limit for interacting particle systems through a duality-based framework and obtain quantitative estimates on the convergence of marginals as well as on correlation functions. In particular, for merely…

Analysis of PDEs · Mathematics 2026-05-05 Nadia Khoury , P. -E. Jabin

We consider deterministic particle dynamics with time evolving weights and their associated Kolmogorov equation and mean-field equation. We prove existence and unique- ness for the limit PDE alongside estimates on the growth of the…

Analysis of PDEs · Mathematics 2026-03-06 Immanuel Ben Porat , José A. Carrillo , Alexandra Holzinger

Motivated by considerations from neuroscience (macroscopic behavior of large ensembles of interacting neurons), we consider a population of mean field interacting diffusions in $\mathbf {R}^m$ in the presence of a random environment and…

Probability · Mathematics 2014-07-03 Eric Luçon , Wilhelm Stannat

We consider a system of $N$ particles whose interactions are characterized by a (weighted) graph $G^N$. Each particle is a node of the graph with an internal state. The state changes according to Markovian dynamics that depend on the states…

Probability · Mathematics 2024-05-15 Sebastian Allmeier , Nicolas Gast

Collective dynamics can be observed among many animal species, and have given rise in the last decades to an active and interdisciplinary field of study. Such behaviors are often modeled by active matter, in which each individual is…

Mathematical Physics · Physics 2021-08-31 Clément Erignoux

This paper continues our survey about the mean-field derivation of the two-dimensional signal-dependent Keller-Segel system studied in [1]. Therefore, we consider the same system of moderately interacting particles as before. The difference…

Probability · Mathematics 2026-05-18 Lukas Bol , Li Chen

In this paper, we are concerned with a class of conservative systems including asymmetric exclusion processes and zero-range processes as examples, where some particles are initially placed on $N$ positions. A particle jumps from a position…

Probability · Mathematics 2024-01-24 Xiaofeng Xue

In this paper, we consider the problem of joint parameter estimation for drift and diffusion coefficients of a stochastic McKean-Vlasov equation and for the associated system of interacting particles. The analysis is provided in a general…

Statistics Theory · Mathematics 2023-06-26 Chiara Amorino , Akram Heidari , Vytautė Pilipauskaitė , Mark Podolskij

We investigate systems of interacting stochastic differential equations with two kinds of heterogeneity: one originating from different weights of the linkages, and one concerning their asymptotic relevance when the system becomes large. To…

Probability · Mathematics 2020-06-02 Carsten Chong , Claudia Klüppelberg

This paper investigates the limit behavior of Markov Decision Processes (MDPs) made of independent particles evolving in a common environment, when the number of particles goes to infinity. In the finite horizon case or with a discounted…

Probability · Mathematics 2009-06-10 Nicolas Gast , Bruno Gaujal

Interacting systems are ubiquitous in nature and engineering, ranging from particle dynamics in physics to functionally connected brain regions. These interacting systems can be modeled by graphs where edges correspond to the interactions…

Machine Learning · Computer Science 2024-01-25 Zhichao Han , Olga Fink , David S. Kammer