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Probabilistic cellular automata with general alphabets possessing a Markov chain as an invariant distribution

Part of: Markov processes Stochastic processes Special processes Topological dynamics

Published online by Cambridge University Press:  10 June 2016

Jérôme Casse
Jérôme Casse*
Affiliation:
Université de Bordeaux
*
* Postal address: LaBRI, Université de Bordeaux, 351 cours de Libération, 33405 Talence cedex, France. Email address: jerome.casse@univ-lorraine.fr
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Abstract

This paper is devoted to probabilistic cellular automata (PCAs) on N,Z or Z / nZ, depending on two neighbors with a general alphabet E (finite or infinite, discrete or not). We study the following question: under which conditions does a PCA possess a Markov chain as an invariant distribution? Previous results in the literature give some conditions on the transition matrix (for positive rate PCAs) when the alphabet E is finite. Here we obtain conditions on the transition kernel of a PCA with a general alphabet E. In particular, we show that the existence of an invariant Markov chain is equivalent to the existence of a solution to a cubic integral equation. One of the difficulties in passing from a finite alphabet to a general alphabet comes from the problem of measurability, and a large part of this work is devoted to clarifying these issues.

Keywords

Probabilistic cellular automatainvariant measureMarkov chain

MSC classification

Primary: 37B15: Cellular automata 60G10: Stationary processes 60J05: Discrete-time Markov processes on general state spaces
Secondary: 60K35: Interacting random processes; statistical mechanics type models; percolation theory
Type
Research Article
Information
Advances in Applied Probability , Volume 48 , Issue 2 , June 2016 , pp. 369 - 391
Copyright
Copyright © Applied Probability Trust 2016 

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