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In the series of models with interacting particles in stochastic geometry, a new contribution presents the facet process which is defined in arbitrary Euclidean dimension. In 2D, 3D specially it is a process of interacting segments, flat…

Probability · Mathematics 2015-04-02 Jakub Vecera , Viktor Benes

The study of time-inhomogeneous Markov jump processes is a traditional topic within probability theory that has recently attracted substantial attention in various applications. However, their flexibility also incurs a substantial…

Probability · Mathematics 2023-11-03 Martin Bladt , Oscar Peralta

The processes of interplant competition within a field are still poorly understood. However, they explain a large part of the heterogeneity in a field and may have longer-term consequences, especially in mixed stands. Modeling can help to…

Analysis of PDEs · Mathematics 2019-06-05 Antonin Della Noce , Amélie Mathieu , Paul-Henry Cournède

We introduce a stochastic dynamics related to the measures that arise in harmonic analysis on the infinite-dimensional unitary group. Our dynamics is obtained as a limit of a sequence of natural Markov chains on Gelfand-Tsetlin graph. We…

Probability · Mathematics 2011-08-19 Vadim Gorin

Consider an interacting particle system indexed by the vertices of a (possibly random) locally finite graph whose vertices and edges are equipped with marks representing parameters of the model such as the environment and initial…

Probability · Mathematics 2024-07-31 Ankan Ganguly , Kavita Ramanan

We present an approach to the dynamics of interacting particle systems, which allows to derive path integral formulas from purely stochastic considerations. We show that the resulting field theory is a dual version of the standard theory of…

Statistical Mechanics · Physics 2008-11-26 Alexandre lefevre , Giulio Biroli

We consider a sequence of Hawkes processes whose excitation measures may depend on the generation, and study its scaling limits in the near-unstable limiting regime. The limiting random measures, characterized via a nonlinear convolutional…

Probability · Mathematics 2026-04-08 Tristan Pace , Gordan Zitkovic

We establish a functional weak law of large numbers for observable macroscopic state variables of interacting particle systems (e.g., voter and contact processes) over fast time-varying sparse random networks of interactions. We show that,…

Probability · Mathematics 2017-03-01 Augusto Almeida Santos , Soummya Kar , José M. F. Moura , João Xavier

In the present work, we explore homogenization techniques for a class of switching diffusion processes whose drift and diffusion coefficients, and jump intensities are smooth, spatially periodic functions; we assume full coupling between…

Probability · Mathematics 2025-07-01 Chetan D. Pahlajani

We consider interacting systems particle driven by i.i.d. fractional Brownian motions, subject to irregular, possibly distributional, pairwise interactions. We show propagation of chaos and mean field convergence to the law of the…

Probability · Mathematics 2025-12-02 Lucio Galeati , Khoa Lê , Avi Mayorcas

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

Hawkes point processes are first-order non-Markovian stochastic models of intermittent bursty dynamics with applications to physical, seismic, epidemic, biological, financial, and social systems. While accounting for positive feedback loops…

Statistical Mechanics · Physics 2023-02-02 Kiyoshi Kanazawa , Didier Sornette

Among the statistical tools for online information diffusion modeling, both epidemic models and Hawkes point processes are popular choices. The former originate from epidemiology, and consider information as a viral contagion which spreads…

Social and Information Networks · Computer Science 2018-05-18 Marian-Andrei Rizoiu , Swapnil Mishra , Quyu Kong , Mark Carman , Lexing Xie

We derive a stochastic partial differential equation that describes the fluctuating behaviour of reaction-diffusion systems of N particles, undergoing Markovian, unary reactions. This generalises the work of Dean [J. Phys. A: Math. and…

Statistical Mechanics · Physics 2025-01-13 Richard E. Spinney , Richard G. Morris

A criterion for proving a strong form of propagation of chaos on the path space, known as entropy chaos, for a general interacting diffusion system is proposed. Our analysis focuses on the class of conservative diffusions introduced by…

Probability · Mathematics 2026-04-17 Luigi Borasi , Francesco Carlo De Vecchi , Stefania Ugolini

This article presents a biological neural network model driven by inhomogeneous Poisson processes accounting for the intrinsic randomness of synapses. The main novelty is the introduction of local interactions: each firing neuron triggers…

Probability · Mathematics 2021-08-17 Maximiliano Altamirano , Roberto Cortez , Matthieu Jonckheere , Lasse Leskelä

This paper presents a stochastic model motivated by the study of a virus-like evolving population with different mutation rates. This is a continuous time birth-death model: the birth processes are mutually-exciting Hawkes processes and the…

Probability · Mathematics 2026-03-10 Rahul Roy , Dharmaraja Selvamuthu , Paola Tardelli

We introduce a heterogeneous formulation of a contagious McKean-Vlasov system, whose inherent heterogeneity comes from asymmetric interactions with a natural and highly tractable structure. It is shown that this formulation characterises…

Probability · Mathematics 2022-09-28 Zachary Feinstein , Andreas Sojmark

In this paper, we study the asymptotic behavior of a fully-coupled slow-fast McKean-Vlasov stochastic system. Using the non-linear Poisson equation on Wasserstein space, we first establish the strong convergence in the averaging principle…

Probability · Mathematics 2022-07-14 Yun Li , Longjie Xie

The random batch method provides an efficient algorithm for computing statistical properties of a canonical ensemble of interacting particles. In this work, we study the error estimates of the fully discrete random batch method, especially…

Probability · Mathematics 2022-09-01 Xuda Ye , Zhennan Zhou