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In this paper, we derive rigorously a non-local cross-diffusion system from an interacting stochastic many-particle system in the whole space. The convergence is proved in the sense of probability by introducing an intermediate particle…

Probability · Mathematics 2023-08-22 Yue Li , Li Chen , Zhipeng Zhang

Hawkes processes are a self-exciting stochastic process used to describe phenomena whereby past events increase the probability of the occurrence of future events. This work presents a flexible approach for modelling a variant of these,…

Methodology · Statistics 2022-08-08 Raiha Browning , Judith Rousseau , Kerrie Mengersen

We study reaction-diffusion systems where diffusion is by jumps whose sizes are distributed exponentially. We first study the Fisher-like problem of propagation of a front into an unstable state, as typified by the A+B $\to$ 2A reaction. We…

Statistical Mechanics · Physics 2009-11-11 Elisheva Cohen , David A. Kessler

This paper considers a multiclass processor-sharing queue with feedback. Jobs arrive according to renewal processes, and service times follow general distributions. Upon service completion, jobs may either depart the system or re-enter as a…

Probability · Mathematics 2025-04-30 Mohamed Ghazali , Abdelghani Ben Tahar , Amal Ezzidani

We examine a distributional fixed-point equation related to a multi-type branching process that is key in the cluster sizes analysis of multivariate heavy-tailed Hawkes processes. Specifically, we explore the tail behavior of its solution…

Probability · Mathematics 2025-04-07 Jose Blanchet , Roger J. A. Laeven , Xingyu Wang , Bert Zwart

In this work we investigate the generic properties of a stochastic linear model in the regime of high-dimensionality. We consider in particular the Vector AutoRegressive model (VAR) and the multivariate Hawkes process. We analyze both…

Statistical Mechanics · Physics 2015-06-11 Iacopo Mastromatteo , Emmanuel Bacry , Jean-François Muzy

We consider continuous state branching processes (CSBP) with additional multiplicative jumps modeling dramatic events in a random environment. These jumps are described by a L\'evy process with bounded variation paths. We construct a…

Probability · Mathematics 2013-12-17 Vincent Bansaye , Juan Carlos Pardo Millan , Charline Smadi

We study a general class of birth-and-death processes with state space $\mathbb{N}$ that describes the size of a population going to extinction with probability one. This class contains the logistic case. The scale of the population is…

Probability · Mathematics 2017-02-20 J. -R. Chazottes , P. Collet , S. Méléard

This article is concerned with the mathematical analysis of a family of adaptive importance sampling algorithms applied to diffusion processes. These methods, referred to as Adaptive Biasing Potential methods, are designed to efficiently…

Probability · Mathematics 2018-05-10 Michel Benaïm , Charles-Edouard Bréhier

Univariate marked Hawkes processes are used to model a range of real-world phenomena including earthquake aftershock sequences, contagious disease spread, content diffusion on social media platforms, and order book dynamics. This paper…

Methodology · Statistics 2026-04-13 Louis Davis , Conor Kresin , Boris Baeumer , Ting Wang

A controlled branching process (CBP) is a modification of the standard Bienaym\'e-Galton-Watson process in which the number of progenitors in each generation is determined by a random mechanism. We consider a CBP starting from a random…

Probability · Mathematics 2024-04-26 González , M. , Martín-Chávez , P. , del Puerto , I

We study the asymptotic behavior of branching diffusion processes in periodic media. For a super-critical branching process, we distinguish two types of behavior for the normalized number of particles in a bounded domain, depending on the…

Probability · Mathematics 2020-03-05 Pratima Hebbar , Leonid Koralov , James Nolen

We study some SDEs derived from the $q\to 1$ limit of a 2D surface growth model called the $q$-Whittaker process. The fluctuations are proven to exhibit Gaussian characteristics that "come down from infinity": After rescaling and…

Probability · Mathematics 2021-01-12 Yu-Ting Chen

A space fractional diffusion-like equation is introduced, which embodies the nonlocality in time, represented by the memory kernel and the non-locality in space. A specific example of the nonlocal term is considered in combination with…

Statistical Mechanics · Physics 2026-01-06 Pece Trajanovski , Irina Petreska , Katarzyna Gorska , Ljupco Kocarev , Trifce Sandev

We considered diffusion-driven processes on small-world networks with distance-dependent random links. The study of diffusion on such networks is motivated by transport on randomly folded polymer chains, synchronization problems in…

Statistical Mechanics · Physics 2007-09-05 Balazs Kozma , Matthew B. Hastings , G. Korniss

Classic results show that the Hawkes self-exciting point process can be viewed as a collection of temporal clusters, where exogenously generated initial events give rise to endogenously driven descendant events. This perspective provides…

Probability · Mathematics 2022-12-12 Andrew Daw

Asymptotic analysis has become a common approach in investigations of reaction-diffusion equations and pattern formation, especially when considering generalizations to the original model, such as spatial heterogeneity, where finding an…

Pattern Formation and Solitons · Physics 2021-04-21 Juraj Kováč , Václav Klika

We consider continuous space-time decay-surge population models which are semi- stochastic processes for which deterministically declining populations, bound to fade away, are rein- vigorated at random times by bursts or surges of random…

Probability · Mathematics 2021-11-09 Branda Goncalves , Thierry Huillet , Eva Löcherbach

We are interested in the long-time behavior of a diploid population with sexual reproduction, characterized by its genotype composition at one bi-allelic locus. The population is modeled by a 3-dimensional birth-and-death process with…

Probability · Mathematics 2013-09-16 Camille Coron

Given a collection of entities (or nodes) in a network and our intermittent observations of activities from each entity, an important problem is to learn the hidden edges depicting directional relationships among these entities. Here, we…

Machine Learning · Statistics 2017-08-01 Triet M Le