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In this paper we analyse a class of nonlinear cross-diffusion systems for two species with local repulsive interactions that exhibit a formal gradient flow structure with respect to the Wasserstein metric. We show that systems where the…

Analysis of PDEs · Mathematics 2019-06-11 M. Burger , J. A. Carrillo , J. -F. Pietschmann , M. Schmidtchen

Extended systems governed by partial differential equations can, under suitable conditions, be approximated by means of sets of ordinary differential equations for global quantities capturing the essential features of the systems dynamics.…

Quantitative Methods · Quantitative Biology 2015-06-18 Juan Belmonte-Beitia , Gabriel F. Calvo , Victor M. Perez-Garcia

A class of parabolic cross-diffusion systems modeling the interaction of an arbitrary number of population species is analyzed in a bounded domain with no-flux boundary conditions. The equations are formally derived from a random-walk…

Analysis of PDEs · Mathematics 2015-02-20 Nicola Zamponi , Ansgar Jüngel

The main aim of this work is to establish an averaging principle for a wide class of interacting particle systems in the continuum. This principle is an important step in the analysis of Markov evolutions and is usually applied for the…

Mathematical Physics · Physics 2022-03-17 Martin Friesen , Yuri Kondratiev

We establish long-time and large-data existence of a suitable weak solution to three-dimensional internal unsteady flows described by Kolmogorov's two-equation model of turbulence. The governing system of equations is completed by initial…

Analysis of PDEs · Mathematics 2019-06-11 Miroslav Bulíček , Josef Málek

Reaction diffusion equations have been used to model a wide range of biological phenomenon related to population spread and proliferation from ecology to cancer. It is commonly assumed that individuals in a population have homogeneous…

Dynamical Systems · Mathematics 2023-04-14 Kyle Nguyen , Erica M. Rutter , Kevin Flores

The large deviation principle on phase space is proved for a class of Markov processes known as random population dynamics with catastrophes. In the paper we study the process which corresponds to the random population dynamics with linear…

Probability · Mathematics 2019-11-18 A. Logachov , O. Logachova , A. Yambartsev

We translate a coagulation-framentation model, describing the dynamics of animal group size distributions, into a model for the population distribution and associate the \blue{nonlinear} evolution equation with a Markov jump process of a…

Populations and Evolution · Quantitative Biology 2020-06-16 Pierre Degond , Maximilian Engel , Jian-Guo Liu , Robert L. Pego

By generalizing Bogolyubov's reduced description method, we suggest a formalism to derive kinetic equations for many-body dissipative systems in external stochastic field. As a starting point, we use a stochastic Liouville equation obtained…

Statistical Mechanics · Physics 2015-07-17 Oleksii Sliusarenko , Alexei Chechkin , Yurii Slyusarenko

We consider heterogeneously interacting diffusive particle systems and their large population limit. The interaction is of mean field type with weights characterized by an underlying graphon. A law of large numbers result is established as…

Probability · Mathematics 2022-10-07 Erhan Bayraktar , Suman Chakraborty , Ruoyu Wu

We consider a class of generalized long-range exclusion processes evolving either on $\mathbb Z$ or on a finite lattice with an open boundary. The jump rates are given in terms of a general kernel depending on both the departure and…

Probability · Mathematics 2024-10-24 Patrícia Gonçalves , Julian Kern , Lu Xu

We study gradient drift-diffusion processes on a probability simplex set with finite state Wasserstein metrics, namely finite state Wasserstein common noises. A fact is that the Kolmogorov transition equation of finite reversible Markov…

Probability · Mathematics 2024-09-20 Wuchen Li

Zabrodin recently proposed a generalization of Dyson Brownian motion to a setting where the particles are confined to a smooth Jordan curve in the plane. In this paper, we discuss a rigorous construction of such a process on a rectifiable…

Probability · Mathematics 2026-03-06 Vladislav Guskov , Mingchang Liu , Fredrik Viklund

Gradient-driven diffusion in crowded, multicomponent mixtures is a topic of high interest because of its role in biological processes such as transport in cell membranes. In partially phase-separated solutions, gradient-driven diffusion…

Soft Condensed Matter · Physics 2017-02-15 Prithviraj Nandigrami , Brandy Grove , Andrew Konya , Robin L. B. Selinger

We show the variational convergence of an irreversible Markov jump process describing a finite stochastic particle system to the solution of a countable infinite system of deterministic time-inhomogeneous quadratic differential equations…

Analysis of PDEs · Mathematics 2025-07-08 Jasper Hoeksema , Chun Yin Lam , André Schlichting

The mean-field approximations of many-boson dynamics are known to be effective in many physical relevant situations. The mathematical justifications of such approximations rely generally on specific considerations which depend too much on…

Mathematical Physics · Physics 2018-10-29 Clément Rouffort

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

Analysis of PDEs · Mathematics 2021-12-01 Mitia Duerinckx

Physical systems that dissipate, mix and develop turbulence also irreversibly transport statistical density. In statistical physics, laws for these processes have a mathematical form and tractability that depends on whether the description…

Statistical Mechanics · Physics 2022-11-16 Swetamber Das , Jason R. Green

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

Crowd flow describes the elementary group behavior of crowds. Understanding the dynamics behind these movements can help to identify various abnormalities in crowds. However, developing a crowd model describing these flows is a challenging…

Computer Vision and Pattern Recognition · Computer Science 2020-08-19 Shreetam Behera , Debi Prosad Dogra , Malay Kumar Bandyopadhyay , Partha Pratim Roy
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