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In the context of interacting particle systems, we study the influence of the action of the semigroup on the concentration property of Lipschitz functions. As an application, this gives a new approach to estimate the relaxation speed to…

Probability · Mathematics 2015-06-30 Jean René Chazottes , Pierre Collet , Frank Redig

In this paper, we analyze the convergence rate of a collapsed Gibbs sampler for crossed random effects models. Our results apply to a substantially larger range of models than previous works, including models that incorporate missingness…

Computation · Statistics 2021-10-22 Swarnadip Ghosh , Chenyang Zhong

In this paper we study the quenched distributions of hitting times for a class of random dynamical systems. We prove that hitting times to dynamically defined cylinders converge to a Poisson point process under the law of random equivariant…

Dynamical Systems · Mathematics 2020-11-30 Harry Crimmins , Benoît Saussol

Many models for point process data are defined through a thinning procedure where locations of a base process (often Poisson) are either kept (observed) or discarded (thinned). In this paper, we go back to the fundamentals of the…

Methodology · Statistics 2024-12-12 Renaud Alie , David A. Stephens , Alexandra M. Schmidt

The asymptotic behaviors of the integrated density of states $N(\lambda)$ of Schr\"odinger operators with nonpositive potentials associated with Gibbs point processes are studied. It is shown that for some Gibbs point processes, the leading…

Probability · Mathematics 2022-10-21 Yuta Nakagawa

For a thought experiment concerning the mixing of two classical gases, Gibbs concluded that the work that can be extracted from mixing is determined by whether or not the gases can be distinguished by a semi-permeable membrane; that is, the…

Quantum Physics · Physics 2020-11-19 Zoë Holmes , Florian Mintert , Janet Anders

We consider a family of determinantal random point processes on the two-dimensional lattice and prove that members of our family can be interpreted as a kind of Gibbs ensembles of nonintersecting paths. Examples include probability measures…

Mathematical Physics · Physics 2015-05-13 Alexei Borodin , Senya Shlosman

Network dynamics with point-process-based interactions are of paramount modeling interest. Unfortunately, most relevant dynamics involve complex graphs of interactions for which an exact computational treatment is impossible. To circumvent…

Probability · Mathematics 2022-11-22 François Baccelli , Michel Davydov , Thibaud Taillefumier

We define a potential-weighted connective constant that measures the effective strength of a repulsive pair potential of a Gibbs point process modulated by the geometry of the underlying space. We then show that this definition leads to…

Probability · Mathematics 2021-09-03 Marcus Michelen , Will Perkins

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

Bayesian hierarchical Poisson models are an essential tool for analyzing count data. However, designing efficient algorithms to sample from the posterior distribution of the target parameters remains a challenging task for this class of…

Methodology · Statistics 2025-02-10 Aldo Gardini , Fedele Greco , Carlo Trivisano

We extend the idea of approximating piecewise smooth univariate functions using rational approximation introduced in \cite{aka_bas-19a} to two-dimensional space. This article aims to implement the novel piecewise Maehly based…

Numerical Analysis · Mathematics 2024-05-07 Akansha Singh

In this article, we fill a gap in the literature regarding quantitative functional central limit theorems (qfCLT) for Hawkes processes by providing an upper bound for the convergence of a nearly unstable Hawkes process toward a…

Probability · Mathematics 2025-06-16 Laure Coutin , Benjamin Massat , Anthony Réveillac

The convergence of a sequence of point processes with dependent points, defined by a symmetric function of iid high-dimensional random vectors, to a Poisson random measure is proved. This also implies the convergence of the joint…

Probability · Mathematics 2024-02-14 Johannes Heiny , Carolin Kleemann

In this work, we adopt a general framework based on the Gibbs posterior to update belief distributions for inverse problems governed by partial differential equations (PDEs). The Gibbs posterior formulation is a generalization of standard…

Computation · Statistics 2019-07-04 Zilong Zou , Sayan Mukherjee , Harbir Antil , Wilkins Aquino

Determinantal point processes (DPPs) are random point processes well-suited for modeling repulsion. In machine learning, the focus of DPP-based models has been on diverse subset selection from a discrete and finite base set. This discrete…

Machine Learning · Statistics 2013-11-14 Raja Hafiz Affandi , Emily B. Fox , Ben Taskar

[B{\l}aszczyszyn, Yogeshwaran and Yukich (2019)] established central limit theorems for geometric statistics of point processes having fast decay dependence. As limit theorems are of limited use unless we understand their errors involved in…

Probability · Mathematics 2022-05-27 Tianshu Cong , Aihua Xia

We revise the encounter-based approach to imperfect diffusion-controlled reactions, which employs the statistics of encounters between a diffusing particle and the reactive region to implement surface reactions. We extend this approach to…

Statistical Mechanics · Physics 2023-10-03 Denis S. Grebenkov

This paper is devoted to the estimation of a vector parametrizing an energy function associated to some "Nearest-Neighbours" Gibbs point process, via the pseudo-likelihood method. We present some convergence results concerning this…

Statistics Theory · Mathematics 2016-08-16 Jean-Michel Billiot , Jean-François Coeurjolly , Rémy Drouilhet

We consider a gas of N particles with a general two-body interaction and confined by an external potential in the mean field or high temperature regime, that is when the inverse temperature satisfies $\beta N \to \kappa \ge 0$ as…

Probability · Mathematics 2019-12-24 Gaultier Lambert