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We consider a (one-dimensional) branching Brownian motion process with a general offspring distribution having at least two moments, and in which all particles have a drift towards the origin where they are immediately absorbed. It is…

Probability · Mathematics 2018-09-13 Oren Louidor , Santiago Saglietti

We consider a system of particles which perform branching Brownian motion with negative drift and are killed upon reaching zero, in the near-critical regime where the total population stays roughly constant with approximately N particles.…

Probability · Mathematics 2013-03-15 Julien Berestycki , Nathanaël Berestycki , Jason Schweinsberg

In this paper we consider Bayesian parameter inference for partially observed fractional Brownian motion (fBM) models. The approach we follow is to time-discretize the hidden process and then to design Markov chain Monte Carlo (MCMC)…

Computation · Statistics 2022-11-02 Mohamed Maama , Ajay Jasra , Hernando Ombao

We consider the behaviour of branching-selection particle systems in the large population limit. The dynamics of these systems is the combination of the following three components: (a) Motion: particles move on the real line according to a…

Probability · Mathematics 2023-11-22 Jean Bérard , Brieuc Frénais

This dissertation examines the impact of a drift {\mu} on Brownian Bees, which is a type of branching Brownian motion that retains only the N closest particles to the origin. The selection effect in the 0-drift system ensures that it…

Probability · Mathematics 2023-04-28 Donald Flynn

We study the maximum of Branching Brownian motion (BBM) with branching rates that vary in space, via a periodic function of a particle's location. This corresponds to a variant of the F-KPP equation in a periodic medium, extensively studied…

Probability · Mathematics 2020-05-22 Eyal Lubetzky , Chris Thornett , Ofer Zeitouni

Particle approximations for certain nonlinear and nonlocal reaction-diffusion equations are studied using a system of Brownian motions with killing. The system is described by a collection of i.i.d. Brownian particles where each particle is…

Probability · Mathematics 2019-05-01 Amarjit Budhiraja , Wai-Tong Louis Fan , Ruoyu Wu

We consider, through PDE methods, branching Brownian motion with drift and absorption. It is well know that there exists a critical drift which separates those processes which die out almost surely and those which survive with positive…

Analysis of PDEs · Mathematics 2014-10-08 Christopher Henderson

We introduce and analyse a two-sided branching-selection particle system which generalises the well-known $N$-particle branching Brownian motion ($N$-BBM) model, which we call the $(N,p)$-BBM, where either the leftmost or rightmost particle…

Probability · Mathematics 2026-04-24 Jacob Mercer

We consider a branching-selection particle system on the real line. In this model the total size of the population at time $n$ is limited by $\exp\left(a n^{1/3}\right)$. At each step $n$, every individual dies while reproducing…

Probability · Mathematics 2018-10-02 Bastien Mallein

The dynamics of temperature fluctuations of a gas of Brownian particles in local equilibrium with a nonequilibrium heat bath, are described using an approach consistent with Boltzmann-Gibbs statistics (BG). We use mesoscopic nonequilibrium…

Statistical Mechanics · Physics 2009-11-13 R. F. Rodriguez , I. Santamaria-Holek

We introduce the stochastic process of incremental multifractional Brownian motion (IMFBM), which locally behaves like fractional Brownian motion with a given local Hurst exponent and diffusivity. When these parameters change as function of…

Statistical Mechanics · Physics 2023-07-27 Jakub Slezak , Ralf Metzler

Branching Brownian Motion describes a system of particles which diffuse in space and split into offsprings according to a certain random mechanism. In virtue of the groundbreaking work by M. Bramson on the convergence of solutions of the…

Probability · Mathematics 2011-06-28 Louis-Pierre Arguin , Anton Bovier , Nicola Kistler

We consider a particle system in continuous time, discrete population, with spatial motion and nonlocal branching. The offspring's weights and their number may depend on the mother's weight. Our setting captures, for instance, the processes…

Probability · Mathematics 2012-10-12 Bertrand Cloez

The paper addresses Brownian motion in the logarithmic potential with time-dependent strength, $U(x,t) = g(t) \log(x)$, subject to the absorbing boundary at the origin of coordinates. Such model can represent kinetics of…

Statistical Mechanics · Physics 2015-09-29 Artem Ryabov , Ekaterina Berestneva , Viktor Holubec

Consider the fractional Brownian Motion (fBM) $B^H=\{B^H(t): t \in [0,1] \}$ with Hurst index $H\in (0,1)$. We construct a probability space supporting both $B^H$ and a fully simulatable process $\hat B_{\epsilon}^H $ such that $$\sup_{t\in…

Probability · Mathematics 2019-02-22 Yi Chen , Jing Dong , Hao Ni

Brownian motion with darning (BMD in abbreviation) is introduced and studied in [4] and [5, Chapter 7]. Roughly speaking, BMD travels across the "darning area" at infinite speed, while it behaves like a regular BM outside of this area. In…

Probability · Mathematics 2022-03-25 Shuwen Lou

Logistic linear mixed model is widely used in experimental designs and genetic analysis with binary traits. Motivated by modern applications, we consider the case with many groups of random effects and each group corresponds to a variance…

Computation · Statistics 2017-11-15 Liuyi Hu , Wenbin Lu , Jin Zhou , Hua Zhou

The resolution of Brownian motion in simulations of micro-particle suspensions can be crucial to reproducing the correct dynamics of individual particles, as well as providing an accurate characterisation of suspension properties. Including…

Fluid Dynamics · Physics 2015-06-16 Eric E. Keaveny

We consider a standard binary branching Brownian motion on the real line. It is known that the maximal position $M_t$ among all particles alive at time $t$, shifted by $m_t = \sqrt{2} t - \frac{3}{2\sqrt{2}} \log t$ converges in law to a…

Probability · Mathematics 2020-07-02 Xinxin Chen , Hui He , Bastien Mallein