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We study approach to the large-time jammed state of the deposited particles in the model of random sequential adsorption. The convergence laws are usually derived from the argument of Pomeau which includes the assumption of the dominance,…

Statistical Mechanics · Physics 2017-11-27 Arjun Verma , Vladimir Privman

We firstly extend the interpretation of feedback communication over stationary finite dimensional Gaussian channels as feedback control systems by showing that, the problem of finding stabilizing feedback controllers with maximal reliable…

Information Theory · Computer Science 2015-12-01 Chong Li , Nicola Elia

We consider a popular nonsmooth formulation of the real phase retrieval problem. We show that under standard statistical assumptions, a simple subgradient method converges linearly when initialized within a constant relative distance of an…

Optimization and Control · Mathematics 2018-01-09 Damek Davis , Dmitriy Drusvyatskiy , Courtney Paquette

The question of the local stability of the (replica-symmetric) amorphous solid state is addressed for a class of systems undergoing a continuous liquid to amorphous-solid phase transition driven by the effect of random constraints. The…

Disordered Systems and Neural Networks · Physics 2009-10-31 Horacio E. Castillo , Paul M. Goldbart , Annette Zippelius

We review and study some of the properties of smooth Gaussian random fields defined on a homogeneous space, under the assumption that the probability distribution is invariant under the isometry group of the space. We first give an…

Probability · Mathematics 2022-04-22 Alexandre Afgoustidis

We prove finite-sample concentration and anti-concentration bounds for dimension estimation using Gaussian kernel sums. Our bounds provide explicit dependence on sample size, bandwidth, and local geometric and distributional parameters,…

Statistics Theory · Mathematics 2026-02-24 Martin Andersson

We prove a pointwise version of the multi-dimensional central limit theorem for convex bodies. Namely, let X be an isotropic random vector in R^n with a log-concave density. For a typical subspace E in R^n of dimension n^c, consider the…

Metric Geometry · Mathematics 2007-08-21 Ronen Eldan , Bo'az Klartag

We use Stein's method to obtain bounds on the rate of convergence for a class of statistics in geometric probability obtained as a sum of contributions from Poisson points which are exponentially stabilizing, i.e. locally determined in a…

Probability · Mathematics 2007-05-23 Mathew D. Penrose , J. E. Yukich

We study the sandpile model in infinite volume on $\mathbb{Z}^d$. In particular, we are interested in the question whether or not initial configurations, chosen according to a stationary measure $\mu$, are $\mu$-almost surely stabilizable.…

Probability · Mathematics 2009-06-16 Anne Fey , Ronald Meester , Frank Redig

We consider the non-overlapping irreversible random sequential adsorption (RSA) process on one-dimensional finite line, which is known also as the car parking process. The probability of each coverage in saturating states is analytically…

Statistical Mechanics · Physics 2008-12-03 Masatomo Iwasa , Kyohei Fukuda

We show that the statistical multifragmentation model with the standard parameterization of the free volume predicts a constant pressure as density approaches the normal nuclear density. This is contrary to the Raduta&Raduta result obtained…

Nuclear Theory · Physics 2007-05-23 A. S. Botvina , I. N. Mishustin

A completely elementary and self-contained proof of convergence of Gaussian multiplicative chaos is given. The argument shows further that the limiting random measure is nontrivial in the entire subcritical phase $(\gamma < \sqrt{2d})$ and…

Probability · Mathematics 2017-10-31 Nathanaël Berestycki

We consider a one-dimensional system of particles, moving at constant velocities chosen independently according to a symmetric distribution on $\{-1,0,+1\}$, and annihilating upon collision -- with, in case of triple collision, a uniformly…

Probability · Mathematics 2022-01-05 John Haslegrave , Laurent Tournier

Transmission of the scalar field through the random medium, represented by the system of randomly distributed dielectric cylinders is calculated numerically. System is mapped to the problem of electronic transport in disordered…

Mesoscale and Nanoscale Physics · Physics 2016-08-31 P. Markos , C. M. Soukoulis

We study the adsorption-desorption of fluid molecules on a solid substrate by introducing a schematic model in which the adsorption/desorption transition probabilities are given by irreversible kinetic constraints with a tunable violation…

Statistical Mechanics · Physics 2019-11-27 Mauro Sellitto

We study the regularity of densities of distributions that are polynomial images of the standard Gaussian measure on $\mathbb{R}^n$. We assume that the degree of a polynomial is fixed and that each variable enters to a power bounded by…

Probability · Mathematics 2020-07-28 Egor Kosov

The velocity of a passive particle in a one-dimensional wave field is shown to converge in law to a Wiener process, in the limit of a dense wave spectrum with independent complex amplitudes, where the random phases distribution is invariant…

Mathematical Physics · Physics 2012-07-12 Yves Elskens

Based on quasi-stationary distribution ideas, a general finite size scaling theory is proposed for discontinuous nonequilibrium phase transitions into absorbing states. Analogously to the equilibrium case, we show that quantities such as,…

Statistical Mechanics · Physics 2015-12-23 M. M. de Oliveira , M. G. E. da Luz , C. E. Fiore

A stationary Gaussian process is said to be long-range dependent (resp., anti-persistent) if its spectral density $f(\lambda)$ can be written as $f(\lambda)=|\lambda|^{-2d}g(|\lambda|)$, where $0<d<1/2$ (resp., $-1/2<d<0$), and $g$ is…

Methodology · Statistics 2012-07-24 Judith Rousseau , Nicolas Chopin , Brunero Liseo

We study high-dimensional asymptotic performance limits of binary supervised classification problems where the class conditional densities are Gaussian with unknown means and covariances and the number of signal dimensions scales faster…

Machine Learning · Statistics 2016-11-17 Mohammad Hossein Rohban , Prakash Ishwar , Birant Orten , William C. Karl , Venkatesh Saligrama