Quasi-reversible Creation-annihilation Models: Colliding Bullet Model with Creations and a Loop Model

We consider a large class of creation-annihilation models that contains, in particular, the colliding bullet model with creations and a loop model. For this large class of creation-annihilation models, we give sufficient conditions on their parameter to be rot(π)-quasi-reversible and to be rot(π/2)-quasi-reversible. Moreover, those conditions assure them that one of their stationary measures is described by a Poisson point process. These results, applied to the colliding bullet model with creations, are the first steps to study its non-empty stationary measure, and, applied to the loop model, prove its invariance according to all the symmetries of the square.

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Publication Details

Journal
Markov Processes And Related Fields
Published
2026-10-29
DOI
https://doi.org/10.61102/1024-2953-mprf.2026.32.3.001
Primary Topic
Stochastic processes and statistical mechanics
Type
article
Field-Weighted Citation Impact
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article

Quasi-reversible Creation-annihilation Models: Colliding Bullet Model with Creations and a Loop Model

J. Casse
Markov Processes And Related Fields
Stochastic processes and statistical mechanics
article

Quasi-reversible Creation-annihilation Models: Colliding Bullet Model with Creations and a Loop Model

J. Casse
article en

Abstract

We consider a large class of creation-annihilation models that contains, in particular, the colliding bullet model with creations and a loop model. For this large class of creation-annihilation models, we give sufficient conditions on their parameter to be rot(π)-quasi-reversible and to be rot(π/2)-quasi-reversible. Moreover, those conditions assure them that one of their stationary measures is described by a Poisson point process. These results, applied to the colliding bullet model with creations, are the first steps to study its non-empty stationary measure, and, applied to the loop model, prove its invariance according to all the symmetries of the square.

Markov Processes And Related Fields(2026 №3 (32))
Centre National de la Recherche Scientifique (FR), Université Paris-Saclay (FR)
Openalex Percentile: Top 7%
Stochastic processes and statistical mechanics
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