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Related papers: Maximal Branching Processes in Random Environment

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We review the theory of regenerative processes, which are processes that can be intuitively seen as comprising of i.i.d.\ cycles. Although we focus on the classical definition, we present a more general definition that allows for some form…

Probability · Mathematics 2014-04-23 Maria Vlasiou

We introduce a branching process in a sparse random environment as an intermediate model between a Galton--Watson process and a branching process in a random environment. In the critical case we investigate the survival probability and…

Probability · Mathematics 2023-06-13 Dariusz Buraczewski , Congzao Dong , Alexander Iksanov , Alexander Marynych

Irreversible random sequential deposition of interacting particles is widely used to model aggregation phenomena in physical, chemical, and biophysical systems. We show that in one dimension the exact time dependent solution of such…

Statistical Mechanics · Physics 2019-06-07 Adrian Baule

We study the distribution of the maximal jump of continuous-state branching processes. Several exact expressions and explicit asymptotics of both the local maximal jump and the global maximal jump are obtained. We also compare the…

Probability · Mathematics 2014-12-16 Xin He , Zenghu Li

It is well known that the behaviour of a branching process is completely described by the generating function of the offspring law and its fixed points. Branching random walks are a natural generalization of branching processes: a branching…

Probability · Mathematics 2016-11-28 Daniela Bertacchi , Fabio Zucca

Subcritical population processes are attracted to extinction and do not have non-trivial stationary distributions, which prompts the study of quasi-stationary distributions (QSDs) instead. In contrast to what generally happens for…

Probability · Mathematics 2026-02-12 Pablo Groisman , Leonardo T. Rolla , Célio Terra

We introduce an algorithm for generating a random sequence of fragmentation trees, which we call the ancestral branching algorithm. This algorithm builds on the recursive partitioning structure of a tree and gives rise to an associated…

Probability · Mathematics 2011-11-02 Harry Crane

We describe particles in a potential by a special diffusion process, the maximal entropy random walk (MERW) on a lattice. Since MERW originates in a variational problem, it shares the linear algebra of Hilbert spaces with quantum mechanics.…

Quantum Physics · Physics 2023-12-29 Manfried Faber

Motivated by a seminal paper of Kesten et al. (1975) we consider a branching process with a geometric offspring distribution with i.i.d. random environmental parameters $A_n$, $n\ge 1$ and size -1 immigration in each generation. In contrast…

Probability · Mathematics 2020-10-21 Sergey Foss , Dmitry Korshunov , Zbigniew Palmowski

In this work, we present a general method to establish properties of multi-dimensional continuous-time Markov chains representing stochastic reaction networks. This method consists of grouping states together (via a partition of the state…

Probability · Mathematics 2025-05-27 Guillaume Ballif , Laurent Pfeiffer , Jakob Ruess

The purpose of this study is to investigate two related spatial branching models with the unbounded branching intensity. The objective is to describe the asymptotic behaviour of the extremal particle.

Probability · Mathematics 2018-06-08 Rafał Meller

The well known maximum-entropy principle due to Jaynes, which states that given mean parameters, the maximum entropy distribution matching them is in an exponential family, has been very popular in machine learning due to its "Occam's…

Machine Learning · Computer Science 2016-07-13 Yuanzhi Li , Andrej Risteski

We present a new modeling paradigm for optimization that we call random field optimization. Random fields are a powerful modeling abstraction that aims to capture the behavior of random variables that live on infinite-dimensional spaces…

Optimization and Control · Mathematics 2022-01-26 Joshua L. Pulsipher , Benjamin R. Davidson , Victor M. Zavala

Herding is a deterministic algorithm used to generate data points that can be regarded as random samples satisfying input moment conditions. The algorithm is based on the complex behavior of a high-dimensional dynamical system and is…

Machine Learning · Statistics 2023-05-10 Hiroshi Yamashita , Hideyuki Suzuki , Kazuyuki Aihara

We study branching random walks in random environment on the $d$-dimensional square lattice, $d \geq 1$. In this model, the environment has finite range dependence, and the population size cannot decrease. We prove limit theorems (laws of…

Probability · Mathematics 2012-01-31 Francis Comets , Serguei Popov

In this work we study a branching particle system of diffusion processes on the real line interacting through their rank in the system. Namely, each particle follows an independent Brownian motion, but only K $\ge$ 1 particles on the far…

Analysis of PDEs · Mathematics 2025-05-14 Mete Demircigil , Milica Tomasevic

The paper has four goals. First, we want to generalize the classical concept of the branching property so that it becomes applicable for historical and genealogical processes (using the coding of genealogies by ($V$-marked) ultrametric…

Probability · Mathematics 2020-05-06 Andreas Greven , Thomas Rippl , Patric Karl Glöde

We consider the evolution of populations under the joint action of mutation and differential reproduction, or selection. The population is modelled as a finite-type Markov branching process in continuous time, and the associated…

Populations and Evolution · Quantitative Biology 2009-02-23 Ellen Baake , Hans-Otto Georgii

We study the critical centered branching random walk with offspring and displacement distributions having finite variance, under minimal assumptions on its structure. We show that the probability that the position of the right-most particle…

Probability · Mathematics 2025-10-15 Thomas Lehéricy

We consider population-size-dependent branching processes (PSDBPs) which eventually become extinct with probability one. For these processes, we derive maximum likelihood estimators for the mean number of offspring born to individuals when…

Statistics Theory · Mathematics 2020-09-22 Peter Braunsteins , Sophie Hautphenne , Carmen Minuesa