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An active Brownian particle is a minimal model for a self-propelled colloid in a dissipative environment. Experiments and simulations show that, in the presence of boundaries and obstacles, active Brownian particle systems approach…

Soft Condensed Matter · Physics 2024-01-17 Caleb G. Wagner , Michael F. Hagan , Aparna Baskaran

We consider a new class of non Markovian processes with a countable number of interacting components. At each time unit, each component can take two values, indicating if it has a spike or not at this precise moment. The system evolves as…

Probability · Mathematics 2015-06-12 Antonio Galves , Eva Löcherbach

In this paper we intend to present a unified treatment of a variety of singular interacting particle systems and their McKean-Vlasov limits. This unified approach is based on the use of the relative entropy on the path space in the spirit…

Analysis of PDEs · Mathematics 2024-12-11 Patrick Cattiaux

We consider the graphon mean-field system introduced in the work of Bayraktar, Chakraborty, and Wu. It is the large-population limit of a heterogeneously interacting diffusive particle system, where the interaction is of mean-field type…

Statistics Theory · Mathematics 2024-03-12 Erhan Bayraktar , Hongyi Zhou

In this work we study a branching particle system of diffusion processes on the real line interacting through their rank in the system. Namely, each particle follows an independent Brownian motion, but only K $\ge$ 1 particles on the far…

Analysis of PDEs · Mathematics 2025-05-14 Mete Demircigil , Milica Tomasevic

A model for the evolution of a large population interacting system is considered in which a marked Poisson processes influences their evolution, together with a Brownian motion. Mean field McKean-Vlasov limits of such system are formulated…

Probability · Mathematics 2024-08-13 Daniel Hernández-Hernández , Joshué Helí Ricalde-Guerrero

As the availability and importance of temporal interaction data--such as email communication--increases, it becomes increasingly important to understand the underlying structure that underpins these interactions. Often these interactions…

Machine Learning · Computer Science 2020-06-16 Elahe Ghalebi , Hamidreza Mahyar , Radu Grosu , Graham W. Taylor , Sinead A. Williamson

In this paper, we study multi-species stochastic interacting particle systems and their mean-field McKean-Vlasov partial differential equations (PDEs) in non-convex landscapes. We discuss the well-posedness of the multi-species SDE system,…

Probability · Mathematics 2025-07-11 Manh Hong Duong , Grigorios A. Pavliotis , Julian Tugaut

In the last decade there has been increasing interest in the fields of random matrices, interacting particle systems, stochastic growth models, and the connections between these areas. For instance, several objects appearing in the limit of…

Mathematical Physics · Physics 2011-04-06 Patrik L. Ferrari , René Frings

Bayesian sampling is an important task in statistics and machine learning. Over the past decade, many ensemble-type sampling methods have been proposed. In contrast to the classical Markov chain Monte Carlo methods, these new methods deploy…

Numerical Analysis · Mathematics 2024-05-14 Shi Chen , Zhiyan Ding , Qin Li

In this paper we discuss the analysis of a cross-diffusion PDE system for a mixture of hard spheres, which was derived by Bruna and Chapman from a stochastic system of interacting Brownian particles using the method of matched asymptotic…

Analysis of PDEs · Mathematics 2017-03-08 Maria Bruna , Martin Burger , Helene Ranetbauer , Marie-Therese Wolfram

Graph-limit theory focuses on the convergence of sequences of graphs when the number of nodes becomes arbitrarily large. This framework defines a continuous version of graphs allowing for the study of dynamical systems on very large graphs,…

Probability · Mathematics 2020-05-20 Julien Petit , Renaud Lambiotte , Timoteo Carletti

This thesis develops exact analytical tools to study strongly correlated stochastic systems, with a focus on extreme value statistics, gap statistics, and full counting statistics in multi-particle processes. A central contribution is the…

Statistical Mechanics · Physics 2025-08-19 Marco Biroli

Interacting particle systems are known for their ability to generate large-scale self-organized structures from simple local interaction rules between each agent and its neighbors. In addition to studying their emergent behavior, a main…

Analysis of PDEs · Mathematics 2024-10-21 Nathalie Ayi , Nastassia Pouradier Duteil , David Poyato

We study systems of interacting Brownian particles in one dimension constructed as the diffusion scaling limits of Fisher's vicious walk models. We define two types of nonintersecting Brownian motions, in which we impose no condition (resp.…

Statistical Mechanics · Physics 2007-05-23 M. Katori , H. Tanemura

A system of interacting Brownian particles subject to short-range repulsive potentials is considered. A continuum description in the form of a nonlinear diffusion equation is derived systematically in the dilute limit using the method of…

Statistical Mechanics · Physics 2017-10-12 Maria Bruna , S. Jonathan Chapman , Martin Robinson

Although real-world complex systems typically interact through sparse and heterogeneous networks, analytic solutions of their dynamics are limited to models with all-to-all interactions. Here, we solve the dynamics of a broad range of…

Disordered Systems and Neural Networks · Physics 2025-01-28 Fernando L. Metz

The goal of this paper is to approximate several kinds of {\it Mckean-Vlasov SDEs} with {\it irregular coefficients} via weakly interacting particle systems. More precisely, propagation of chaos and convergence rate of Euler-Maruyama scheme…

Probability · Mathematics 2019-06-06 Jianhai Bao , Xing Huang

In this paper we derive the continuum limit of a multiple-species, interacting particle system by proving a $\Gamma$-convergence result on the interaction energy as the number of particles tends to infinity. As the leading application, we…

Analysis of PDEs · Mathematics 2020-06-09 Patrick van Meurs

We consider large uniform labeled random graphs in different classes with prescribed decorations in their modular decomposition. Our main result is the estimation of the number of copies of every graph as an induced subgraph. As a…

Combinatorics · Mathematics 2023-10-25 Théo Lenoir