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We consider a branching Brownian motion evolving in $\mathbb{R}^d$. We prove that the asymptotic behaviour of the maximal displacement is given by a first ballistic order, plus a logarithmic correction that increases with the dimension $d$.…

Probability · Mathematics 2015-10-27 Bastien Mallein

We obtain a large deviations principle for the self-intersection local times for a symmetric random walk in dimension d>4. As an application, we obtain moderate deviations for random walk in random sceneries in some region of parameters.

Probability · Mathematics 2008-12-30 Amine Asselah

The densest amorphous packing of rigid particles is known as random close packing. It has long been appreciated that higher densities are achieved by using collections of particles with a variety of sizes. The variety of sizes is often…

Soft Condensed Matter · Physics 2015-01-13 Kenneth W. Desmond , Eric R. Weeks

We study the asymptotic behaviour of the maximum interpoint distance of random points in a planar bounded set with an unique major axis and a boundary behaving like an ellipse at the endpoints. Our main result covers the case of uniformly…

Probability · Mathematics 2015-05-08 Michael Schrempp

Let \( D \) be a strongly connected digraph. The average distance of a vertex \( v \) in \( D \) is defined as the arithmetic mean of the distances from \( v \) to all other vertices in \( D \). The remoteness \( \rho(D) \) of \( D \) is…

Combinatorics · Mathematics 2025-10-13 Sufiyan Mallu

Finding the most powerful node in a dynamic random network, the largest set in a partition-valued stochastic process, or the largest family in an evolving population at a given time, can be a very difficult problem. This is particularly the…

Probability · Mathematics 2020-09-09 Cécile Mailler , Peter Mörters , Anna Senkevich

For a sample of absolutely bounded i.i.d. random variables with a continuous density the cumulative distribution function of the sample variance is represented by a univariate integral over a Fourier series. If the density is a polynomial…

Statistics Theory · Mathematics 2008-10-10 T. Royen

Nearest-neighbor methods are fundamental to classical and modern machine learning, yet their geometric properties are typically analyzed under independent sampling. In this paper, we study the nearest-neighbor radii under dependent…

Machine Learning · Computer Science 2026-05-15 Yuanyuan Gao , Yilong Hou , Zhexiao Lin

Let $X_1,X_2, \ldots $ be independent random uniform points in a bounded domain $A \subset \mathbb{R}^d$ with smooth boundary. Define the coverage threshold $R_n$ to be the smallest $r$ such that $A$ is covered by the balls of radius $r$…

Probability · Mathematics 2022-01-12 Mathew D. Penrose

We consider a large family of branching-selection particle systems. The branching rate of each particle depends on its rank and is given by a function $b$ defined on the unit interval. There is also a killing measure $D$ supported on the…

Probability · Mathematics 2021-12-28 P. Groisman , N. Soprano-Loto

We revisit the maximum range sum (MaxRS) problem: given a set $P$ of $n$ weighted points in $\mathbb{R}^d$ and a range $Q$ (typically axis-aligned $d$-box or $d$-ball), the goal is to place $Q$ to maximize the total weight of points in…

Computational Geometry · Computer Science 2025-09-22 Rachana Gusain , Saladi Rahul , Aditya Subramanian

Systems which consist of many localized constituents interacting with each other can be represented by complex networks. Consistently, network science has become highly popular in vast fields focusing on natural, artificial and social…

Statistical Mechanics · Physics 2022-06-29 Rute Oliveira , Samuraí Brito , Luciano R. da Silva , Constantino Tsallis

We give an upper bound in O(d ^((n+1)/2)) for the number of critical points of a normal random polynomial with degree d and at most n variables. Using the large deviation principle for the spectral value of large random matrices we obtain…

Numerical Analysis · Mathematics 2010-07-12 Jean-Pierre Dedieu , Gregorio Malajovich

We study the dual variants of the Erd\H{o}s's distinct distances and unit distance problems. Instead of considering distances determined by points, we consider simplex volumes determined by hyperplanes. We investigate: (1) the maximum…

Combinatorics · Mathematics 2026-03-11 Koki Furukawa

With the aim of generalizing histogram statistics to higher dimensional cases, density estimation via discrepancy based sequential partition (DSP) has been proposed to learn an adaptive piecewise constant approximation defined on a binary…

Machine Learning · Statistics 2025-12-23 Zhengyang Lei , Lirong Qu , Sihong Shao , Yunfeng Xiong

We introduce the concept of a hyperuniformity disorder length that controls the variance of volume fraction fluctuations for randomly placed windows of fixed size. In particular, fluctuations are determined by the average number of…

Soft Condensed Matter · Physics 2017-09-18 A. T. Chieco , R. Dreyfus , D. J. Durian

We introduce a simple geometric model which describes the kinetics of fragmentation of d-dimensional objects. In one dimension our model coincides with the random scission model and show a simple scaling behavior in the long-time limit. For…

Condensed Matter · Physics 2009-10-22 P. L. Krapivsky , E. Ben-Naim

One of the main contributions of this paper is to illustrate how large deviation theory can be used to determine the equilibrium distribution of a basic droplet model that underlies a number of important models in material science and…

Probability · Mathematics 2015-09-11 Richard S. Ellis , Shlomo Ta'asan

Random dynamical systems (RDS) evolve by a dynamical rule chosen independently with a certain probability, from a given set of deterministic rules. These dynamical systems in an interval reach a steady state with a unique well-defined…

Statistical Mechanics · Physics 2020-09-21 M. S. Shesha Gopal , Soumitro Banerjee , P. K. Mohanty

A set of points with finite density is constructed in $\mathbb{R}^d$, with $d\geq2$, by adding points to a Poisson process such that any line segment of length $O\left(\varepsilon^{-(d-1)}\ln\varepsilon^{-1}\right)$ in $\mathbb{R}^d$ will…

Metric Geometry · Mathematics 2024-12-17 Kirill Kashkan