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Let $\Xi$ be a set of centers chosen according to a Poisson point process in $\mathbb R^d$. Consider the allocation of $\mathbb R^d$ to $\Xi$ which is stable in the sense of the Gale-Shapley marriage problem, with the additional feature…

Probability · Mathematics 2021-11-16 Daniel Andrés Díaz-Pachón

Let \Xi be a discrete set in R^d. Call the elements of \Xi centers. The well-known Voronoi tessellation partitions R^d into polyhedral regions (of varying volumes) by allocating each site of R^d to the closest center. Here we study…

Probability · Mathematics 2007-05-23 Christopher Hoffman , Alexander E. Holroyd , Yuval Peres

Let $\Xi$ be a discrete set in ${\mathbb{R}}^d$. Call the elements of $\Xi$ centers. The well-known Voronoi tessellation partitions ${\mathbb{R}}^d$ into polyhedral regions (of varying sizes) by allocating each site of ${\mathbb{R}}^d$ to…

Probability · Mathematics 2007-05-23 Christopher Hoffman , Alexander E. Holroyd , Yuval Peres

Let $\Xi$ be the set of points (we call the elements of $\Xi$ centers) of Poisson process in $\R^d$, $d\geq 2$, with unit intensity. Consider the allocation of $\R^d$ to $\Xi$ which is stable in the sense of Gale-Shapley marriage problem…

Probability · Mathematics 2012-01-31 Marcelo Ventura Freire , Serguei Popov , Marina Vachkovskaia

Suppose that red and blue points occur as independent homogeneous Poisson processes in R^d. We investigate translation-invariant schemes for perfectly matching the red points to the blue points. For any such scheme in dimensions d=1,2, the…

Probability · Mathematics 2008-03-15 Alexander E. Holroyd , Robin Pemantle , Yuval Peres , Oded Schramm

For d>=3, we construct a non-randomized, fair and translation-equivariant allocation of Lebesgue measure to the points of a standard Poisson point process in R^d, defined by allocating to each of the Poisson points its basin of attraction…

Probability · Mathematics 2017-03-14 Sourav Chatterjee , Ron Peled , Yuval Peres , Dan Romik

We prove a large deviation principle for the point process associated to $k$-element connected components in $\mathbb R^d$ with respect to the connectivity radii $r_n\to\infty$. The random points are generated from a homogeneous Poisson…

Probability · Mathematics 2022-10-19 Christian Hirsch , Takashi Owada

We establish a large deviation principle for a reflected Poisson driven SDE. Our motivation is to study in a forthcoming paper the problem of exit of such a process from the basin of attraction of a locally stable equilibrium associated…

Probability · Mathematics 2020-03-09 Etienne Pardoux , Brice Samegni-Kepgnou

We obtain large deviation results for non-uniformly expanding maps with non-flat singularities or criticalities and for partially hyperbolic non-uniformly expanding attracting sets. That is, given a continuous function we consider its space…

Dynamical Systems · Mathematics 2018-09-14 V Araujo , M J Pacifico

This paper develops the large deviations theory for the point process associated with the Euclidean volume of $k$-nearest neighbor balls centered around the points of a homogeneous Poisson or a binomial point processes in the unit cube. Two…

Probability · Mathematics 2022-10-25 Christian Hirsch , Taegyu Kang , Takashi Owada

Consider a graph on randomly scattered points in an arbitrary space, with two points $x,y$ connected with probability $\phi(x,y)$. Suppose the number of points is large but the mean number of isolated points is $O(1)$. We give general…

Probability · Mathematics 2017-09-21 Mathew D. Penrose

We derive large- and moderate-deviation results in random networks given as planar directed navigations on homogeneous Poisson point processes. In this non-Markovian routing scheme, starting from the origin, at each consecutive step a…

Probability · Mathematics 2026-04-13 Partha Pratim Ghosh , Benedikt Jahnel , Sanjoy Kumar Jhawar

We study the asymptotic behavior of the maximum interpoint distance of random points in a $d$-dimensional set with a unique diameter and a smooth boundary at the poles. Instead of investigating only a fixed number of $n$ points as $n$ tends…

Probability · Mathematics 2017-09-13 Michael Schrempp

We present a comprehensive discussion of the phenomenology of flavourful axions, including both standard Peccei-Quinn (PQ) axions, associated with the solution to the strong $CP$ problem, and non-standard axion-like particles (ALPs). We…

High Energy Physics - Phenomenology · Physics 2018-09-26 Fredrik Björkeroth , Eung Jin Chun , Stephen F. King

We investigate the distribution of critical points of certain isotropic random functions $\Phi$ on $\mathbb{R}^m$. We show that the distribution of critical points of $\Phi(Rx)$, suitably normalized, converge a.s. and $L^2$ as random…

Probability · Mathematics 2024-12-05 Liviu I. Nicolaescu

Consider an unlimited homogeneous medium disturbed by points generated via Poisson process. The neighborhood of a point plays an important role in spatial statistics problems. Here, we obtain analytically the distance statistics to $k$th…

Statistical Mechanics · Physics 2015-08-11 Cristiano Roberto Fabri Granzotti , Alexandre Souto Martinez

We establish large deviation estimates for Poisson driven models of infectious disease, and apply those estimates to the time of exit from the basin of attraction of an endemic equilibrium. We apply our results to the classical SIRS model.

Probability · Mathematics 2016-02-10 Peter Kratz , Etienne Pardoux

Consider the continuous greedy paths model: given a $d$-dimensional Poisson point process with positive marks interpreted as masses, let $\mathrm P(\ell)$ denote the maximum mass gathered by a path of length $\ell$ starting from the origin.…

Probability · Mathematics 2025-03-04 Julien Verges

We consider the random point processes on a measure space X defined by the Gibbs measures associated to a given sequence of N-particle Hamiltonians H^{(N)}. Inspired by the method of Messer-Spohn for proving concentration properties for the…

Mathematical Physics · Physics 2016-10-27 Robert J. Berman

We formulate large deviations principle (LDP) for diffusion pair $(X^\epsilon,\xi^\epsilon)=(X_t^\epsilon,\xi_t^\epsilon)$, where first component has a small diffusion parameter while the second is ergodic Markovian process with fast time.…

Probability · Mathematics 2007-05-23 R. Liptser
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