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Consider a non-symmetric generalized diffusion $X(\cdot)$ in ${\bbR}^d$ determined by the differential operator $A(\msx)=-\sum_{ij} \partial_ia_{ij}(\msx)\partial_j +\sum_i b_i(\msx)\partial_i$. In this paper the diffusion process is…

Probability · Mathematics 2010-03-16 Nedzad Limić

The paper deals with the asymptotic properties of a random jump process in a high contrast periodic medium in $\mathbb R^d$, $d\geq 1$. We show that if the coordinates of the random jump process in $\mathbb R^d$ are equipped with an extra…

Probability · Mathematics 2024-02-13 Andrey Piatnitski , Elena Zhizhina

This work explores a synchronization-like phenomenon induced by common noise for continuous-time Markov jump processes given by chemical reaction networks. A corresponding random dynamical system is formulated in a two-step procedure, at…

Dynamical Systems · Mathematics 2022-07-05 Maximilian Engel , Guillermo Olicón-Méndez , Nathalie Unger , Stefanie Winkelmann

We prove a functional limit theorem for Markov chains that, in each step, move up or down by a possibly state dependent constant with probability $1/2$, respectively. The theorem entails that the law of every one-dimensional regular…

Probability · Mathematics 2020-05-13 Stefan Ankirchner , Thomas Kruse , Mikhail Urusov

We study a mutliscale jump process introduced in a work by Crudu, Debussche, Muller and Radulescu. Using an adequate coupling, we are able to prove the strong convergence, for the uniform topology, to a piecewise deterministic Markov…

Probability · Mathematics 2026-03-03 Baptiste Nicolas Huguet

We consider Markov chains on general state spaces in stationary random environment which are defined by a random mapping that is contractive up to a bounded perturbation. We prove their convergence to a limiting law, providing convergence…

Probability · Mathematics 2025-12-18 Attila Lovas , Miklós Rásonyi , Lionel Truquet

This paper is concerned with the development of rigorous approximations to various expectations associated with Markov chains and processes having non-stationary transition probabilities. Such non-stationary models arise naturally in…

Probability · Mathematics 2018-05-07 Zeyu Zheng , Harsha Honnappa , Peter W. Glynn

Given an irreducible discrete-time Markov chain on a finite state space, we consider the largest expected hitting time $T(\alpha)$ of a set of stationary measure at least $\alpha$ for $\alpha\in(0,1)$. We obtain tight inequalities among the…

Probability · Mathematics 2015-10-29 Simon Griffiths , Ross J. Kang , Roberto Imbuzeiro Oliveira , Viresh Patel

Consideration is given to the three different analytical methods for the computation of upper bounds for the rate of convergence to the limiting regime of one specific class of (in)homogeneous continuous-time Markov chains. This class is…

In this short paper, we consider discrete-time Markov chains on lattices as approximations to continuous-time diffusion processes. The approximations can be interpreted as finite difference schemes for the generator of the process. We…

Probability · Mathematics 2016-11-08 Christoph Reisinger

We study inhomogeneous continuous-time weakly ergodic Markov chains with a finite state space. We introduce the notion of a Markov chain with the regular structure of an infinitesimal matrix and study the sharp upper bounds on the rate of…

Probability · Mathematics 2020-02-17 A. I. Zeifman , Y. A. Satin , K. M. Kiseleva

We study the approximation of a Markov chain on a reduced state space, for both discrete- and continuous-time Markov chains. In this context, we extend the existing theory of formal error bounds for the approximated transient distributions.…

Probability · Mathematics 2025-02-12 Fabian Michel , Markus Siegle

We study normal approximations for a class of discrete-time occupancy processes, namely, Markov chains with transition kernels of product Bernoulli form. This class encompasses numerous models which appear in the complex networks…

Probability · Mathematics 2018-11-13 Liam Hodgkinson , Ross McVinish , Philip K. Pollett

The main purpose of this work is to study self-similar branching Markov chains. First we will construct such a process. Then we will establish certain Limit Theorems using the theory of self-similar Markov processes.

Probability · Mathematics 2008-01-24 Nathalie Krell

We study a limit behavior of a sequence of Markov processes (or Markov chains) such that their distributions outside of any neighborhood of a "singular" point attract to some probability law. In any neighborhood of this point the behavior…

Probability · Mathematics 2015-09-14 Andrey Pilipenko , Yuriy Prykhodko

Motivated by applications in Markov chain Monte Carlo, we discuss what it means for one Markov chain to be an approximation to another. Specifically included in that discussion are situations in which a Markov chain with continuous state…

Probability · Mathematics 2007-05-23 Mark Jerrum

We develop criteria for recurrence and transience of one-dimensional Markov processes which have jumps and oscillate between $+\infty$ and $-\infty$. The conditions are based on a Markov chain which only consists of jumps (overshoots) of…

Probability · Mathematics 2020-04-17 Björn Böttcher

For a wide class of continuous-time Markov processes, including all irreducible hypoelliptic diffusions evolving on an open, connected subset of $\RL^d$, the following are shown to be equivalent: (i) The process satisfies (a slightly weaker…

Probability · Mathematics 2016-04-27 Ioannis Kontoyiannis , Sean P. Meyn

We derive explicit upper bounds for the $\bar{d}$-distance between a chain of infinite order and its canonical $k$-steps Markov approximation. Our proof is entirely constructive and involves a "coupling from the past" argument. The new…

Probability · Mathematics 2012-01-16 Sandro Gallo , Matthieu Lerasle , Daniel Yasumasa Takahashi

We compute the stationary distribution of a continuous-time Markov chain which is constructed by gluing together two finite, irreducible Markov chains by identifying a pair of states of one chain with a pair of states of the other and…

Probability · Mathematics 2015-10-22 Bence Mélykúti , Peter Pfaffelhuber