Structural Properties of Gibbsian Point Processes in Abstract Spaces

Steffen Betsch ()
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Steffen Betsch: Karlsruhe Institute of Technology (KIT)

Journal of Theoretical Probability, 2023, vol. 36, issue 4, 2501-2563

Abstract: Abstract In the language of random counting measures, many structural properties of the Poisson process can be studied in arbitrary measurable spaces. We provide a similarly general treatise of Gibbs processes. With the GNZ equations as a definition of these objects, Gibbs processes can be introduced in abstract spaces without any topological structure. In this general setting, partition functions, Janossy densities, and correlation functions are studied. While the definition covers finite and infinite Gibbs processes alike, the finite case allows, even in abstract spaces, for an equivalent and more explicit characterization via a familiar series expansion. Recent generalizations of factorial measures to arbitrary measurable spaces, where counting measures cannot be written as sums of Dirac measures, likewise allow to generalize the concept of Hamiltonians. The DLR equations, which completely characterize a Gibbs process, as well as basic results for the local convergence topology, are also formulated in full generality. We prove a new theorem on the extraction of locally convergent subsequences from a sequence of point processes and use this statement to provide existence results for Gibbs processes in general spaces with potentially infinite range of interaction. These results are used to guarantee the existence of Gibbs processes with cluster-dependent interactions and to prove a recent conjecture concerning the existence of Gibbsian particle processes.

Keywords: Gibbs processes; Point process theory; Disagreement percolation; Hamiltonians; Particle processes (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10959-023-01262-9

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