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Representations of branching Markov processes and their measure-valued limits in terms of countable systems of particles are constructed for models with spatially varying birth and death rates. Each particle has a location and a "level,"…

Probability · Mathematics 2011-04-11 Thomas G. Kurtz , Eliane R. Rodrigues

We study individual-based dynamics in finite populations, subject to randomly switching environmental conditions. These are inspired by models in which genes transition between on and off states, regulating underlying protein dynamics.…

Statistical Mechanics · Physics 2016-05-18 Peter G. Hufton , Yen Ting Lin , Tobias Galla , Alan J. McKane

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

We define and study one-dimensional model of irreversible aggregation of particles obeying a discrete-time kinetics which is a special limit of the generalized Totally Asymmetric Simple Exclusion Process (gTASEP) on open chains. The model…

Statistical Mechanics · Physics 2017-05-10 Nadezhda Zh. Bunzarova , Nina Ch. Pesheva

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

In this work we construct the stationary measure of the N species totally asymmetric simple exclusion process in a matrix product formulation. We make the connection between the matrix product formulation and the queueing theory picture of…

Probability · Mathematics 2009-11-13 Martin R. Evans , Pablo A. Ferrari , Kirone Mallick

Stochastic phenomena occurring within charged particle beams can be handled using the Vlasov-Fokker-Planck generalization of the Vlasov equation. In particular, this non-deterministic approach can deal with effects due to Coulomb scattering…

Accelerator Physics · Physics 2023-03-29 Jürgen Struckmeier

The infinitesimal transition probability operator for a continuous-time discrete-state Markov process, $\mathcal{Q}$, can be decomposed into a symmetric and a skew-symmetric parts. As recently shown for the case of diffusion processes,…

Mathematical Physics · Physics 2013-04-09 Hong Qian

We consider totally asymmetric simple exclusion processes with n types of particle and holes ($n$-TASEPs) on $\mathbb {Z}$ and on the cycle $\mathbb {Z}_N$. Angel recently gave an elegant construction of the stationary measures for the…

Probability · Mathematics 2011-11-10 Pablo A. Ferrari , James B. Martin

We obtain a new relation between the distributions $\mu_t$ at different times $t\ge 0$ of the continuous-time TASEP (Totally Asymmetric Simple Exclusion Process) started from the step initial configuration. Namely, we present a…

Probability · Mathematics 2021-02-18 Leonid Petrov , Axel Saenz

We consider a composite medium, which consists of a homogeneous matrix containing a statistically homogeneous set of multimodal spherical inclusions. This model is used to represent the morphology of heterogeneous solid propellants (HSP)…

Materials Science · Physics 2015-03-20 V. A. Buryachenko , T. L. Jackson , G. Amadio

We introduce a multi-species generalization of the symmetric simple exclusion process with open boundaries. This model possesses the property of being integrable and appears as physically relevant because the boundary conditions can be…

Statistical Mechanics · Physics 2017-02-01 Matthieu Vanicat

We define a new mass transport model on a one-dimensional lattice of size $N$ with continuous masses at each site. The lattice is connected to mass reservoirs of different `chemical potentials' at the two ends. The mass transfer dynamics in…

Statistical Mechanics · Physics 2023-02-01 Rahul Dandekar , Anupam Kundu

This paper generalizes the notion of stochastic order to a relation between probability measures over arbitrary measurable spaces. This generalization is motivated by the observation that for the stochastic ordering of two stationary Markov…

Probability · Mathematics 2008-06-24 Lasse Leskelä

The Simple Inclusion Process (SIP) interpolates between two well-known lattice gas models: the independent random walkers and the Kipnis-Marchioro-Presutti model. Here we study large deviations of nonstationary mass transfer in the SIP at…

Statistical Mechanics · Physics 2025-10-14 Eldad Bettelheim , Baruch Meerson

Recently, an Enskog-type kinetic theory for Vicsek-type models for self-propelled particles has been proposed [T. Ihle, Phys. Rev. E 83, 030901 (2011)]. This theory is based on an exact equation for a Markov chain in phase space and is not…

Statistical Mechanics · Physics 2015-07-22 Thomas Ihle

Given a matrix of distribution functions and a quasi-stochastic matrix, i.e. an irreducible nonnegative matrix with maximal eigenvalue one and associated unique positive left and right eigenvectors, the article studies the properties of an…

Probability · Mathematics 2015-08-28 Gerold Alsmeyer

Consider a lattice of n sites arranged around a ring, with the $n$ sites occupied by particles of weights $\{1,2,\dots,n\}$; the possible arrangements of particles in sites thus corresponds to the $n!$ permutations in $S_n$. The…

Combinatorics · Mathematics 2021-02-02 Donghyun Kim , Lauren Williams

We consider a strictly substochastic matrix or an stochastic matrix with absorbing states. By using quasi-stationary distributions one shows there is a canonical associated stationary Markov chain. Based upon $2-$stringing representation of…

Probability · Mathematics 2019-10-03 Servet Martínez

We study a class of multi-stage stochastic programs, which incorporate modeling features from Markov decision processes (MDPs). This class includes structured MDPs with continuous action and state spaces. We extend policy graphs to include…

Machine Learning · Computer Science 2026-04-09 David P. Morton , Oscar Dowson , Bernardo K. Pagnoncelli