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We use a model whose rules were inspired by population genetics, the random capability growth model, to describe the statistical details observed in experiments of fragmentation of brittle platelike objects, and in particular the existence…

Statistical Mechanics · Physics 2016-12-21 M. A. F. Gomes , Viviane M. de Oliveira

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

We consider a Markovian growth process on a partially ordered set $\Lambda$, equivalent to last passage percolation (LPP) with independent (not necessarily identical) exponentially distributed weights on the elements of $\Lambda$. Such a…

Probability · Mathematics 2026-03-26 Tanner J. Reese , Sunder Sethuraman

The multiplicities of the decomposition of the product of an arbitrary number $n$ of spin $s$ states into irreducible $SU(2)$ representations are computed. Two complementary methods are presented, one based on random walks in representation…

High Energy Physics - Theory · Physics 2020-03-06 Alexios P. Polychronakos , Konstantinos Sfetsos

We study the high temperature phase of a family of typed branching diffusions initially studied in [Ast\'{e}risque 236 (1996) 133--154] and [Lecture Notes in Math. 1729 (2000) 239--256 Springer, Berlin]. The primary aim is to establish some…

Probability · Mathematics 2007-05-23 Y. Git , J. W. Harris , S. C. Harris

Inspired by biological dynamics, we consider a growth Markov process taking values on the space of rooted binary trees, similar to the Aldous-Shields model. Fix $n\ge 1$ and $\beta>0$. We start at time 0 with the tree composed of a root…

Cell Behavior · Quantitative Biology 2012-08-14 C. Landim , R. D. Portugal , B. F. Svaiter

We study the behaviour of a natural measure defined on the leaves of the genealogical tree of some branching processes, namely self-similar growth-fragmentation processes. Each particle, or cell, is attributed a positive mass that evolves…

Probability · Mathematics 2019-08-13 François Gaston Ged

In this note we re-visit the fundamental question of the strong law of large numbers and central limit theorem for processes in continuous time with conditional stationary and independent increments. For convenience we refer to them as…

Probability · Mathematics 2026-02-05 Andreas E. Kyprianou , Victor Rivero

Recently introduced and studied in arXiv:2407.07888, a self-similar Markov tree (ssMt) is a random decorated tree that vastly generalises the fragmentation tree. We study here the critical case that was left aside in arXiv:2407.07888.…

Probability · Mathematics 2026-03-18 Nicolas Curien , Xingjian Hu , Dongjian Qian

We solve the problem of constructing an asymptotic global confidence region for the means and the covariance matrices of the reproduction distributions involved in a supercritical multitype branching process. Our approach is based on a…

Statistics Theory · Mathematics 2007-06-13 F. Maaouia , A. Touati

Consider a sequence of Markov processes $X^1, X^2,...$ with state space $E$, where $X^N$ has a strong drift to $D \subseteq E$, such that $\Phi(X^N)$ is slow for some appropriate $\Phi: E\to D$. Using the method of martingale problems, we…

Probability · Mathematics 2026-02-19 Samuel Ayomide Adeosun , Peter Pfaffelhuber

We show uniqueness of the spine of a Fleming-Viot particle system under minimal assumptions on the driving process. If the driving process is a continuous time Markov process on a finite space, we show that asymptotically, when the number…

Probability · Mathematics 2015-07-27 Mariusz Bieniek , Krzysztof Burdzy

Using the foundations laid down in Hardy and Harris (2006) ["A new formulation of the spine approach in branching diffusions", arXiv:math.PR/0611054], we present new spine proofs of the L^p-convergence p>=1) of some key `additive'…

Probability · Mathematics 2007-05-23 Robert Hardy , Simon C. Harris

The goal of this paper has two-folds. First, we establish skeleton and spine decompositions for superprocesses whose underlying processes are general symmetric Hunt processes. Second, we use these decompositions to obtain weak and strong…

Probability · Mathematics 2017-09-05 Zhen-Qing Chen , Yan-Xia Ren , Ting Yang

This paper is the second in a series of papers which combine graphical modelling and marked spatial point patterns. Extending the previous results of \cite Eckardt (2016a), we introduce a marked spatial dependence graph model which depicts…

Applications · Statistics 2016-09-29 Matthias Eckardt , Jorge Mateu

We consider collections of $N$ chordal random curves obtained from a critical lattice model on a planar graph, in the limit when a fine-mesh graph approximates a simply-connected domain. We define and study candidates for such limits in…

Mathematical Physics · Physics 2019-03-26 Alex Karrila

The theory of ``Markov-up'' processes is being developed. This is a new class of stochastic processes with ``partial'' markovian features; it could also be called ``one-sided Markov''. Such a behavior may be found in the real world and in…

Probability · Mathematics 2024-07-01 D. O. Kalikaeva

We consider uniform random permutations in classes having a finite combinatorial specification for the substitution decomposition. These classes include (but are not limited to) all permutation classes with a finite number of simple…

The growth-fragmentation equation models systems of particles that grow and split as time proceeds. An important question concerns the large time asymptotic of its solutions. Doumic and Escobedo ($2016$) observed that when growth is a…

Probability · Mathematics 2019-04-30 Benedetta Cavalli

A multitype Dawson-Watanabe process is conditioned, in subcritical and critical cases, on non-extinction in the remote future. On every finite time interval, its distribution is absolutely continuous with respect to the law of the…

Probability · Mathematics 2011-12-05 Nicolas Champagnat , Sylvie Roelly
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