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Related papers: Cluster expansions for Gibbs point processes

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We introduce a new type of cluster expansion which generalizes a previous formula of Brydges and Kennedy. The method is especially suited for performing a phase-space multiscale expansion in a just renormalizable theory, and allows the…

High Energy Physics - Theory · Physics 2009-07-09 A. Abdesselam , V. Rivasseau

We introduce and analyse a class of fragmentation-coalescence processes defined on finite systems of particles organised into clusters. Coalescent events merge multiple clusters simultaneously to form a single larger cluster, while…

Probability · Mathematics 2017-01-31 Andreas E. Kyprianou , Steven W. Pagett , Tim Rogers

The class of random-cluster models is a unification of a variety of stochastic processes of significance for probability and statistical physics, including percolation, Ising, and Potts models; in addition, their study has impact on the…

Probability · Mathematics 2007-05-23 Geoffrey Grimmett

We show that the chaos representation of some Compound Poisson Type processes displays an underlying intrinsic combinatorial structure, partly independent of the chosen process. From the computational viewpoint, we solve the arising…

Probability · Mathematics 2016-11-08 L. Dello Schiavo

We study cluster algebras with principal coefficient systems that are associated to unpunctured surfaces. We give a direct formula for the Laurent polynomial expansion of cluster variables in these cluster algebras in terms of perfect…

Representation Theory · Mathematics 2008-10-21 Gregg Musiker , Ralf Schiffler

The present report extends the method of fixed point clustering (Phys.Rev. E 61,5, R4691-4693, 2000) by introducing an indirect criterion for the number of clusters. The derived probability function allows an objective distinction of…

Chaotic Dynamics · Physics 2007-05-23 A. Hutt , F. Kruggel

We review some recent progress on applications of Cluster Expansions. We focus on a system of classical particles living in a continuous medium and interacting via a stable and tempered pair potential. We review the cluster expansion in…

Mathematical Physics · Physics 2023-04-26 Dimitrios Tsagkarogiannis

In order to quantify higher-order correlations of the galaxy cluster distribution we use a complete family of additive measures which give scale-dependent morphological information. Minkowski functionals can be expressed analytically in…

We consider empirical multi-dimensional Rare Events Point Processes that keep track both of the time occurrence of extremal observations and of their severity, for stochastic processes arising from a dynamical system, by evaluating a given…

Dynamical Systems · Mathematics 2017-09-19 Ana Cristina Moreira Freitas , Jorge Milhazes Freitas , Mário Magalhães

We give a new criterion for a classical gas with a repulsive pair potential to exhibit uniqueness of the infinite volume Gibbs measure and analyticity of the pressure. Our improvement on the bound for analyticity is by a factor $e^2$ over…

Mathematical Physics · Physics 2022-11-01 Marcus Michelen , Will Perkins

We study the properties of 2D fibre clusters and networks formed by deposition processes. We first examine the growth and scaling properties of single clusters. We then consider a network of such clusters, whose spatial distribution obeys…

Condensed Matter · Physics 2009-10-28 N. Provatas , T. Ala-Nissila , M. J. Alava

In this paper, we propose a new comparison tool for spatial homogeneity of point processes, based on the joint examination of void probabilities and factorial moment measures. We prove that determinantal and permanental processes, as well…

Probability · Mathematics 2014-04-23 Bartlomiej Blaszczyszyn , D. Yogeshwaran

Making use of a recent complete calculation of a chiral six-point correlation function C(z) in a rectangle we calculate various quantities of interest for percolation (SLE parameter \kappa = 6) and many other two-dimensional critical…

Mathematical Physics · Physics 2011-09-13 Jacob J. H. Simmons , Peter Kleban , Steven M. Flores , Robert M. Ziff

We consider a mixture of non-overlapping rods of different lengths $\ell_k$ moving in $\mathbb{R}$ or $\mathbb{Z}$. Our main result are necessary and sufficient convergence criteria for the expansion of the pressure in terms of the…

Mathematical Physics · Physics 2015-09-28 Sabine Jansen

We consider a system of classical particles confined in a box $\Lambda\subset\mathbb{R}^d$ with zero boundary conditions interacting via a stable and regular pair potential. Based on the validity of the cluster expansion for the canonical…

Probability · Mathematics 2021-03-30 Giuseppe Scola

We present sufficient conditions for sums of dependent point processes to converge in distribution to a Poisson process. This extends the classical result of Grigelionis [Theory Probab. Appl. 8 (1963) 172--182] for sums of uniformly null…

Probability · Mathematics 2007-05-23 Matthew O. Jones , Richard F. Serfozo

The cluster expansion formalism used in materials science is reconstructed on an axiomatic basis with the aims of clarifying underlying concepts and improving computational procedures, and without using conventional cluster functions.…

Materials Science · Physics 2022-10-21 Paul E. Lammert , Vincent H. Crespi

We prove central limit theorems (CLT) for empirical processes of extreme values cluster functionals as in Drees and Rootz\'en (2010). We use coupling properties enlightened for Dedecker \& Prieur's $\tau-$dependence coefficients in order to…

Probability · Mathematics 2016-02-29 Paul Doukhan , José Gregorio Gómez

Change-point models deal with ordered data sequences. Their primary goal is to infer the locations where an aspect of the data sequence changes. In this paper, we propose and implement a nonparametric Bayesian model for clustering…

Methodology · Statistics 2025-02-12 Ana Carolina da Cruz , Camila P. E. de Souza

Asynchronous event sequence clustering aims to group similar event sequences in an unsupervised manner. Mixture models of temporal point processes have been proposed to solve this problem, but they often suffer from overfitting, leading to…

Machine Learning · Computer Science 2024-11-08 Yiwei Dong , Shaoxin Ye , Yuwen Cao , Qiyu Han , Hongteng Xu , Hanfang Yang