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We consider systems of agents interacting through topological interactions. These have been shown to play an important part in animal andhuman behavior. Precisely, the system consists of a finite number of particles characterized by their…

Mathematical Physics · Physics 2017-11-22 Adrien Blanchet , Pierre Degond

Deterministic rate equations are widely used in the study of stochastic, interacting particles systems. This approach assumes that the inherent noise, associated with the discreteness of the elementary constituents, may be neglected when…

Statistical Mechanics · Physics 2012-01-26 David A. Kessler , Nadav M. Shnerb

We establish the existence of martingale solutions to a class of stochastic conservation equations. The underlying models correspond to random perturbations of kinetic models for collective motion such as the Cucker-Smale and Motsch-Tadmor…

Probability · Mathematics 2020-07-06 Arnaud Debussche , Angelo Rosello

In this paper, we investigate a generalised model of $N$ particles undergoing second-order non-local interactions on a lattice. Our results have applications across many research areas, including the modelling of migration, information…

Quantitative Methods · Quantitative Biology 2023-01-20 Andrei Sontag , Tim Rogers , Christian A. Yates

We describe the macroscopic behaviour of a particle system with long-range interactions. We describe conditions on the interaction strength in dependency of the distance of the particles, such that the scaling limit of the particle system…

Probability · Mathematics 2015-12-21 Anton Bovier , Carina Geldhauser

Understanding the properties of the stochastic phase field models is crucial to model processes in several practical applications, such as soft matters and phase separation in random environments. To describe such random evolution, this…

Numerical Analysis · Mathematics 2023-03-13 Jianbo Cui , Dianming Hou , Zhonghua Qiao

This paper is concerned with the mean-field limit for the gradient flow evolution of particle systems with pairwise Riesz interactions, as the number of particles tends to infinity. Based on a modulated energy method, using regularity and…

Analysis of PDEs · Mathematics 2016-07-06 Mitia Duerinckx

A detailed study of the mean-field solution of Langevin equations with multiplicative noise is presented. Three different regimes depending on noise-intensity (weak, intermediate, and strong-noise) are identified by performing a…

Statistical Mechanics · Physics 2009-11-11 Miguel A. Munoz , Francesca Colaiori , Claudio castellano

In the context of interacting particle systems, we study the influence of the action of the semigroup on the concentration property of Lipschitz functions. As an application, this gives a new approach to estimate the relaxation speed to…

Probability · Mathematics 2015-06-30 Jean René Chazottes , Pierre Collet , Frank Redig

The study of the normalized sum of random variables and its asymptotic behaviour has been and continues to be a central chapter in probability and statistical mechanics. When those variables are independent the central limit theorem ensures…

Mathematical Physics · Physics 2012-12-18 M. Fedele

We consider the long-time behavior of a population of mean-field oscillators modeling the activity of interacting excitable neurons in large population. Each neuron is represented by its voltage and recovery variables, which are solution to…

Probability · Mathematics 2019-06-24 Eric Luçon , Christophe Poquet

Particle-based stochastic reaction-diffusion (PBSRD) models are a popular approach for studying biological systems involving both noise in the reaction process and diffusive transport. In this work we derive coarse-grained deterministic…

Probability · Mathematics 2021-09-02 Samuel A. Isaacson , Jingwei Ma , Konstantinos Spiliopoulos

This paper first establishes a fundamental mean-square convergence theorem for general one-step numerical approximations of L\'{e}vy noise driven stochastic differential equations with non-globally Lipschitz coefficients. Then two novel…

Numerical Analysis · Mathematics 2019-07-24 Ziheng Chen , Siqing Gan , Xiaojie Wang

This paper is devoted to investigating the random dynamics of stochastic discrete long-wave-short-wave resonance equations, which are characterized by the following features: $(1)$ the equations contain locally Lipschitz nonlinear coupling…

Probability · Mathematics 2026-03-18 Xia Pan , Jianhua Huang , Juntao Wu , Jiangwei Zhang

Spatially extended population dynamics models that incorporate intrinsic noise serve as case studies for the role of fluctuations and correlations in biological systems. Including spatial structure and stochastic noise in predator-prey…

Statistical Mechanics · Physics 2018-01-09 Ulrich Dobramysl , Mauro Mobilia , Michel Pleimling , Uwe C. Täuber

In contrast to the neutral population cycles of the deterministic mean-field Lotka--Volterra rate equations, including spatial structure and stochastic noise in models for predator-prey interactions yields complex spatio-temporal structures…

Populations and Evolution · Quantitative Biology 2013-10-16 Ulrich Dobramysl , Uwe C. Tauber

Understanding under what conditions interacting populations, whether they be plants, animals, or viral particles, coexist is a question of theoretical and practical importance in population biology. Both biotic interactions and…

Populations and Evolution · Quantitative Biology 2011-04-26 Sebastian J. Schreiber , Michel Benaïm , Kolawolé A. S. Atchadé

We prove the convergence of $ \nN $-particle systems of Brownian particles with logarithmic interaction potentials onto a system described by the infinite-dimensional stochastic differential equation (ISDE). % For this proof we present two…

Probability · Mathematics 2017-06-14 Yosuke Kawamoto , Hirofumi Osada

Cooperative effects of periodic force and noise in globally Cooperative effects of periodic force and noise in globally coupled systems are studied using a nonlinear diffusion equation for the number density. The amplitude of the order…

Chaotic Dynamics · Physics 2009-11-07 Hidetsugu Sakaguchi

We consider a data-driven formulation of the classical discrete-time stochastic control problem. Our approach exploits the natural structure of many such problems, in which significant portions of the system are uncontrolled. Employing the…

Optimization and Control · Mathematics 2025-08-25 Boris Baros , Samuel N. Cohen , Christoph Reisinger