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Related papers: Random interlacement is a factor of i.i.d

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In a coalescing random walk, a set of particles make independent random walks on a graph. Whenever one or more particles meet at a vertex, they unite to form a single particle, which then continues the random walk through the graph.…

Data Structures and Algorithms · Computer Science 2016-12-28 Colin Cooper , Robert Elsasser , Hirotaka Ono , Tomasz Radzik

We construct an infinite volume spatial random permutation $(\mathsf X,\sigma)$, where $\mathsf X\subset\mathbb R^d$ is locally finite and $\sigma:\mathsf X\to \mathsf X$ is a permutation, associated to the formal Hamiltonian $$ H(\mathsf…

Mathematical Physics · Physics 2021-09-02 Inés Armendáriz , Pablo A. Ferrari , Sergio Yuhjtman

We consider continuous time random interlacements on $\mathbb{Z}^d$, $d \ge 3$, and characterize the distribution of the corresponding stationary random field of occupation times. When d = 3, we relate this random field to the…

Probability · Mathematics 2012-10-30 Alain-Sol Sznitman

Let \alpha ([0,1]^p) denote the intersection local time of p independent d-dimensional Brownian motions running up to the time 1. Under the conditions p(d-2)<d and d\ge 2, we prove lim_{t\to\infty}t^{-1}\log P\bigl{\alpha([0,1]^p)\ge…

Probability · Mathematics 2007-05-23 Xia Chen

We define two families of Poissonian soups of bidirectional trajectories on $\mathbb{Z}^2$, which can be seen to adequately describe the local picture of the trace left by a random walk on the two-dimensional torus $(\mathbb{Z}/N…

Probability · Mathematics 2017-05-05 Pierre-François Rodriguez

In this article, we study the pointwise asymptotic behavior of iterated convolutions on the one dimensional lattice Z. We generalize the so-called local limit theorem in probability theory to complex valued sequences. A sharp rate of…

Probability · Mathematics 2025-02-25 Lucas Coeuret

This paper studies a statistical network model generated by a large number of randomly sized overlapping communities, where any pair of nodes sharing a community is linked with probability $q$ via the community. In the special case with…

Probability · Mathematics 2018-06-26 Joona Karjalainen , Johan S. H. van Leeuwaarden , Lasse Leskelä

We introduce a new directed graph model for social networks, based on the transitivity of triads. In the Iterated Local Directed Transitivity (ILDT) model, new nodes are born over discrete time-steps, and inherit the link structure of their…

Social and Information Networks · Computer Science 2020-04-07 Anthony Bonato , Daniel W. Cranston , Melissa Huggan , Trent Marbach , Raja Mutharasan

Influence Diagrams (ID) are a flexible tool to represent discrete stochastic optimization problems, including Markov Decision Process (MDP) and Partially Observable MDP as standard examples. More precisely, given random variables considered…

Optimization and Control · Mathematics 2019-07-08 Axel Parmentier , Victor Cohen , Vincent Leclère , Guillaume Obozinski , Joseph Salmon

A growing random graph is constructed by successively sampling without replacement an element from the pool of virtual vertices and edges. At start of the process the pool contains $N$ virtual vertices and no edges. Each time a vertex is…

Probability · Mathematics 2024-02-29 Michael Farber , Alexander Gnedin , Wajid Mannan

A Neyman-Scott process is a special case of a Cox process. The latent and observable stochastic processes are both Poisson processes. We consider a deep Neyman-Scott process in this paper, for which the building components of a network are…

Machine Learning · Statistics 2022-05-10 Chengkuan Hong , Christian R. Shelton

Let $d\geq 3$ be fixed and $G$ be a large random $d$-regular graph on $n$ vertices. We show that if $n$ is large enough then the entry distribution of every almost eigenvector $v$ of $G$ (with entry sum 0 and normalized to have length…

Probability · Mathematics 2016-07-19 Agnes Backhausz , Balazs Szegedy

We consider a generalization of a one-dimensional stochastic process known in the physical literature as L\'evy-Lorentz gas. The process describes the motion of a particle on the real line in the presence of a random array of marked points,…

Probability · Mathematics 2016-04-12 Alessandra Bianchi , Giampaolo Cristadoro , Marco Lenci , Marilena Ligabò

Although the study of weak convergence of superpositions of point processes to the Poisson process dates back to the work of Grigelionis in 1963, it was only recently that Schuhmacher [Stochastic Process. Appl. 115 (2005) 1819--1837]…

Probability · Mathematics 2011-05-10 Louis H. Y. Chen , Aihua Xia

Ancestral graph models, introduced by Richardson and Spirtes (2002), generalize both Markov random fields and Bayesian networks to a class of graphs with a global Markov property that is closed under conditioning and marginalization. By…

Methodology · Statistics 2012-07-19 Mathias Drton , Thomas S. Richardson

Consider a measure $\mu_\lambda = \sum_x \xi_x \delta_x$ where the sum is over points $x$ of a Poisson point process of intensity $\lambda$ on a bounded region in $d$-space, and $\xi_x$ is a functional determined by the Poisson points near…

Probability · Mathematics 2013-02-05 Mathew D. Penrose , Andrew R. Wade

We consider a continuous-time random walk which is defined as an interpolation of a random walk on a point process on the real line. The distances between neighboring points of the point process are i.i.d. random variables in the normal…

Probability · Mathematics 2020-01-08 Alessandra Bianchi , Marco Lenci , Françoise Pène

Recently for a class of critically intermittent random systems a phase transition was found for the finiteness of the absolutely continuous invariant measure. The systems for which this result holds are characterized by the interplay…

Dynamical Systems · Mathematics 2022-07-25 Benthen Zeegers

Let S_{n,k} denote the random geometric graph obtained by placing points inside a square of area n according to a Poisson point process of intensity 1 and joining each such point to the k=k(n) points of the process nearest to it. In this…

Probability · Mathematics 2013-09-18 Victor Falgas-Ravry

We prove that the marginal densities of a global probability mass function in a primal normal factor graph and the corresponding marginal densities in the dual normal factor graph are related via local mappings. The mapping depends on the…

Machine Learning · Statistics 2020-07-15 Mehdi Molkaraie