AbstractWe consider a system of particles moving independently on a countable state space, according to a general (non-space-homogeneous) Markov process. Under mild conditions, the number of particles at each site will converge to a product of independent Poisson distributions; this corresponds to settling to an ideal gas. We derive bounds on the rate of this convergence. In particular, we prove that the variation distance to stationarity decreases proportionally to the sum of squares of the probabilities of each particle to be at a given site. We then apply these bounds to some examples. Our methods include a simple use of the Chen-Stein lemma about Poisson convergence. Our results require certain strong hypotheses, which further work migh...
. We develop quantitative bounds on rates of convergence for continuoustime Markov processes on gene...
AbstractThis paper gives an upper bound for a Wasserstein distance between the distributions of a pa...
AbstractThis study shows that when a point process is partitioned into certain uniformly sparse subp...
AbstractWe consider a system of particles moving independently on a countable state space, according...
.46>1. Introduction. A standard question in Markov process theory is the existence of, and conve...
AbstractWe consider infinite systems of independent Markov chains as processes on the space of parti...
AbstractConsider an infinite collection of particles travelling in d-dimensional Euclidean space and...
The attached file may be somewhat different from the published versionInternational audienceIn this ...
In this paper we give bounds on the total variation distance from convergence of a continuous time p...
AbstractWe give a new sufficient condition for convergence to a Poisson distribution of a sequence o...
The paper is concerned with the equilibrium distributions of continuous-time density dependent Marko...
This dissertation aims to investigate several aspects of the Poisson convergence: Poisson approximat...
AbstractConsider a discrete-time x2-process, i.e. a process defined as the sum of squares of indepen...
We consider infinite systems of independent Markov chains as processes on the space of particle conf...
AbstractBy means of a distributional limit theorem Arjas and Haara (1987) have shown that the total ...
. We develop quantitative bounds on rates of convergence for continuoustime Markov processes on gene...
AbstractThis paper gives an upper bound for a Wasserstein distance between the distributions of a pa...
AbstractThis study shows that when a point process is partitioned into certain uniformly sparse subp...
AbstractWe consider a system of particles moving independently on a countable state space, according...
.46>1. Introduction. A standard question in Markov process theory is the existence of, and conve...
AbstractWe consider infinite systems of independent Markov chains as processes on the space of parti...
AbstractConsider an infinite collection of particles travelling in d-dimensional Euclidean space and...
The attached file may be somewhat different from the published versionInternational audienceIn this ...
In this paper we give bounds on the total variation distance from convergence of a continuous time p...
AbstractWe give a new sufficient condition for convergence to a Poisson distribution of a sequence o...
The paper is concerned with the equilibrium distributions of continuous-time density dependent Marko...
This dissertation aims to investigate several aspects of the Poisson convergence: Poisson approximat...
AbstractConsider a discrete-time x2-process, i.e. a process defined as the sum of squares of indepen...
We consider infinite systems of independent Markov chains as processes on the space of particle conf...
AbstractBy means of a distributional limit theorem Arjas and Haara (1987) have shown that the total ...
. We develop quantitative bounds on rates of convergence for continuoustime Markov processes on gene...
AbstractThis paper gives an upper bound for a Wasserstein distance between the distributions of a pa...
AbstractThis study shows that when a point process is partitioned into certain uniformly sparse subp...