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Markovian loop clusters on graphs

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arxiv 1211.0300 v3 pith:4EGJA7AR submitted 2012-11-01 math.PR

classification math.PR
keywords clusterslooploopsmarkovprocessensemblesgraphgraphs
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abstract

We study the loop clusters induced by Poissonian ensembles of Markov loops on a finite or countable graph (Markov loops can be viewed as excursions of Markov chains with a random starting point, up to re-rooting). Poissonian ensembles are seen as a Poisson point process of loops indexed by 'time'. The evolution in time of the loop clusters defines a coalescent process on the vertices of the graph. After a description of some general properties of the coalescent process, we address several aspects of the loop clusters defined by a simple random walk killed at a constant rate on three different graphs: the integer number line $\mathbb{Z}$, the integer lattice $\mathbb{Z}^d$ with $d\geq 2$ and the complete graph. These examples show the relations between Poissonian ensembles of Markov loops and other models: renewal process, percolation and random graphs.

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  1. Loop clusters on complete graphs

    math.PR 2025-04 conditional novelty 6.0 of 10

    In the loop soup on the complete graph K_n, the number of clusters of size d converges to a mixed Poisson law with mixing variable exp(-dZ/κ), and clusters larger than n^{1-ε} appear almost surely.

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