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We give a stochastic model for the fragmentation phase of a snow avalanche. We construct a fragmentation-branching process related to the avalanches, on the set of all fragmentation sizes introduced by J. Bertoin. A fractal property of this…

Probability · Mathematics 2016-02-17 Lucian Beznea , Madalina Deaconu , Oana Lupascu

The purpose of the present work is twofold. First, we develop the theory of general self-similar growth-fragmentation processes by focusing on martingales which appear naturally in this setting and by recasting classical results for…

Probability · Mathematics 2017-12-13 Jean Bertoin , Timothy Budd , Nicolas Curien , Igor Kortchemski

We consider a simple discrete-time Markov chain with values in $[0,\infty)^{Z^d}$. The Markov chain describes various interesting examples such as oriented percolation, directed polymers in random environment, time discretizations of binary…

Probability · Mathematics 2009-06-26 Nobuo Yoshida

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

At high levels, the asymptotic distribution of a stationary, regularly varying Markov chain is conveniently given by its tail process. The latter takes the form of a geometric random walk, the increment distribution depending on the sign of…

Methodology · Statistics 2014-12-11 Holger Drees , Johan Segers , Michał Warchoł

A new sufficient condition is proved for the existence of stochastic semigroups generated by the sum of two unbounded operators. It is applied to one-dimensional piecewise deterministic Markov processes, where we also discuss the existence…

Analysis of PDEs · Mathematics 2009-07-07 Michael C. Mackey , Marta Tyran-Kaminska

Fragmentation processes are part of a broad class of models describing the evolution of a system of particles which split apart at random. These models are widely used in biology, materials science and nuclear physics, and their asymptotic…

Probability · Mathematics 2020-07-23 Quan Shi , Alexander R. Watson

We address the problem of Lyapunov function construction for a class of continuous-time Markov chains with affine transition rates, typically encountered in stochastic chemical kinetics. Following an optimization approach, we take advantage…

Probability · Mathematics 2014-12-30 Andreas Milias-Argeitis , Mustafa Khammash

Spatial birth-and-death processes with a finite number of particles are obtained as unique solutions to certain stochastic equations. Conditions are given for existence and uniqueness of such solutions, as well as for continuous dependence…

Probability · Mathematics 2015-02-25 Viktor Bezborodov

This paper is devoted to the study of generalised time-fractional evolution equations involving Caputo type derivatives. Using analytical methods and probabilistic arguments we obtain well-posedness results and stochastic representations…

Analysis of PDEs · Mathematics 2022-05-03 M. E. Hernández-Hernández , V. N. Kolokoltsov , L. Toniazzi

We develop a practical approach to establish the stability, that is, the recurrence in a given set, of a large class of controlled Markov chains. These processes arise in various areas of applied science and encompass important numerical…

Statistics Theory · Mathematics 2015-02-02 Christophe Andrieu , Vladislav B. Tadić , Matti Vihola

We consider a class of stochastic dynamical systems, called piecewise deterministic Markov processes, with states $(x, \s)\in \O\times \G$, $\O$ being a region in $\bbR^d$ or the $d$--dimensional torus, $\G$ being a finite set. The…

Statistical Mechanics · Physics 2009-02-25 Alessandra Faggionato , Davide Gabrielli , Marco Ribezzi Crivellari

We present an investigation of stochastic evolution in which a family of evolution equations in $L^1$ are driven by continuous-time Markov processes. These are examples of so-called piecewise deterministic Markov processes (PDMP's) on the…

Probability · Mathematics 2020-12-01 Paweł Klimasara , Michael C. Mackey , Andrzej Tomski , Marta Tyran-Kamińska

Markovian growth-fragmentation processes describe a family of particles which can grow larger or smaller with time, and occasionally split in a conservative manner. They were introduced in a work of Bertoin, where special attention was…

Probability · Mathematics 2016-02-17 Jean Bertoin , Robin Stephenson

This paper presents an elementary proof of stochastic stability of a discrete-time reversible Markov chain starting from a Foster-Lyapunov drift condition. Besides its relative simplicity, there are two salient features of the proof: (i) it…

Probability · Mathematics 2020-05-19 Amirhossein Taghvaei , Prashant G. Mehta

Markovian growth-fragmentation processes introduced by Bertoin model a system of growing and splitting cells in which the size of a typical cell evolves as a Markov process $X$ without positive jumps. We find that two growth-fragmentation…

Probability · Mathematics 2020-02-05 Quan Shi

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

In this paper, we consider the evolution of an (infinitely large) population under recombination and additional evolutionary forces, modelled by a measure-valued ordinary differential equation. We provide a stochastic representation for the…

Probability · Mathematics 2024-10-03 Frederic Alberti

We develop the idea of non-Markovian CTRW (continuous time random walk) approximation to the evolution of interacting particle systems, which leads to a general class of fractional kinetic measure-valued evolutions with variable order. We…

Probability · Mathematics 2022-06-07 Vassili N. Kolokoltsov , Marianna S. Troeva

In this paper we consider the problem of computing the stationary distribution of nearly completely decomposable Markov processes, a well-established area in the classical theory of Markov processes with broad applications in the design,…

Numerical Analysis · Mathematics 2025-06-19 Vasileios Kalantzis , Mark S. Squillante , Chai Wah Wu