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Growth-fragmentation processes describe the evolution of systems of cells which grow continuously and fragment suddenly; they are used in models of cell division and protein polymerisation. Typically, we may expect that in the long run, the…

Probability · Mathematics 2021-01-22 Jean Bertoin , Alexander Watson

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 study the evolution of a particle system whose genealogy is given by a supercritical continuous time Galton--Watson tree. The particles move independently according to a Markov process and when a branching event occurs, the offspring…

Probability · Mathematics 2012-02-20 Vincent Bansaye , Jean-François Delmas , Laurence Marsalle , Viet Chi Tran

Spatial birth-and-death processes with time dependent rates are obtained as solutions to certain stochastic equations. The existence, uniqueness, uniqueness in law and the strong Markov property of unique solutions are proven when the…

Probability · Mathematics 2022-04-22 Viktor Bezborodov , Luca Di Persio

We study a Markovian model for the random fragmentation of an object. At each time, the state consists of a collection of blocks. Each block waits an exponential amount of time with parameter given by its size to some power $\alpha$,…

Probability · Mathematics 2016-08-11 Christina Goldschmidt , Bénédicte Haas

We provide explicit conditions, in terms of the transition kernel of its driving particle, for a Markov branching process to admit a scaling limit toward a self-similar growth-fragmentation with negative index. We also derive a scaling…

Probability · Mathematics 2019-12-10 Benjamin Dadoun

We consider a strong Markov process with killing and prove an approximation method for the distribution of the process conditioned not to be killed when it is observed. The method is based on a Fleming-Viot type particle system with…

Probability · Mathematics 2013-04-04 Denis Villemonais

We show that all local martingales with respect to the initially enlarged natural filtration of a vector of multivariate point processes can be weakly represented up to the minimum among the explosion times of the components. We also prove…

Probability · Mathematics 2021-07-12 Antonella Calzolari , Barbara Torti

The continuous time Markov process considered in this paper belongs to a class of population models with linear growth and catastrophes. There, the catastrophes happen at the arrival times of a Poisson process, and at each catastrophe time,…

Probability · Mathematics 2019-05-14 A. Logachov , O. Logachova , A. Yambartsev

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

We propose and investigate a simple model which describes the kinetics of aggregation of Brownian particles with stochastic self-replication. An exact solution and the scaling theory are presented alongside numerical simulation which fully…

Statistical Mechanics · Physics 2013-10-28 M. K. Hassan , M. Z. Hassan , N. Islam

We define a Markov process on the partitions of $[n]=\{1,\ldots,n\}$ by drawing a sample in $[n]$ at each time of a Poisson process, by merging blocks that contain one of these points and by leaving all other blocks unchanged. This…

Probability · Mathematics 2018-09-03 Sophie Lemaire

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

We consider a self-similar fragmentation process in which the generic particle of size $x$ is replaced at probability rate $x^\alpha$, by its offspring made of smaller particles, where $\alpha$ is some positive parameter. The total of…

Probability · Mathematics 2007-05-23 Jean Bertoin , Alexander Gnedin

We consider a Markovian evolution on point processes, the $\Psi$--process, on the unit interval in which points are added according to a rule that depends only on the spacings of the existing point configuration. Having chosen a spacing, a…

Probability · Mathematics 2020-07-01 Pascal Maillard , Elliot Paquette

Brownian motion is the only random process which is Gaussian, stationary and Markovian. Dropping the Markovian property, i.e. allowing for memory, one obtains a class of processes called fractional Brownian motion, indexed by the Hurst…

Statistical Mechanics · Physics 2016-07-27 Mathieu Delorme , Kay Jörg Wiese

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

We consider the fragmentation process with mass loss and discuss self-similar properties of the arising structure both in time and space, focusing on dimensional analysis. This exhibits a spectrum of mass exponents $\theta$, whose exact…

Statistical Mechanics · Physics 2009-11-07 M. K. Hassan , J. Kurths

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

Strong positional correlations between particles render the diffusion of a tracer particle in a single file anomalous and non-Markovian. While ensemble average observables of tracer particles are nowadays well understood, little is known…

Statistical Mechanics · Physics 2018-11-15 Alessio Lapolla , Aljaz Godec