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Related papers: Small gaps of GOE

200 papers

Extremal spacings between eigenvalues of random unitary matrices of size N pertaining to circular ensembles are investigated. Explicit probability distributions for the minimal spacing for various ensembles are derived for N = 4. We study…

Mathematical Physics · Physics 2013-11-13 Marek Smaczynski , Tomasz Tkocz , Marek Kus , Karol Zyczkowski

The statistical distribution of levels of an integrable system is claimed to be a Poisson distribution. In this paper, we numerically generate an ensemble of N dimensional random diagonal matrices as a model for regular systems. We evaluate…

Exactly Solvable and Integrable Systems · Physics 2011-09-27 A. A. Abul-Magd , A. Y. Abul-Magd

This paper deals with the homogenization of the Poisson equation in a bounded domain of $\mathbb{R}^d$, $d>2$, which is perforated by a random number of small spherical holes with random radii and positions. We show that for a class of…

Analysis of PDEs · Mathematics 2018-03-28 Arianna Giunti , Richard Höfer , Juan J. L. Velázquez

The distribution of the ratios of consecutive eigenvalue spacings of random matrices has emerged as an important tool to study spectral properties of many-body systems. This article numerically investigates the eigenvalue ratios…

Disordered Systems and Neural Networks · Physics 2022-07-13 Ankit Mishra , Tanu Raghav , Sarika Jalan

In this article, we give explicit bounds on the Wasserstein and the Kolmogorov distances between random variables lying in the first chaos of the Poisson space and the standard Normal distribution, using the results proved by Last, Peccati…

Probability · Mathematics 2026-01-14 Mahmoud Khabou , Giovanni Luca Torrisi

We show that the set of atoms of the limiting empirical marginal distribution in the random $2$-SAT model is $\mathbb Q \cap (0,1)$, for all clause-to-variable densities up to the satisfiability threshold. While for densities up to $1/2$,…

Probability · Mathematics 2024-10-24 Noela Müller , Ralph Neininger , Haodong Zhu

We establish Gaussian limits for general measures induced by binomial and Poisson point processes in d-dimensional space. The limiting Gaussian field has a covariance functional which depends on the density of the point process. The general…

Probability · Mathematics 2007-05-23 Yu. Baryshnikov , J. E. Yukich

A simple lower bound to the capacity of the discrete-time Poisson channel with average energy $\es$ is derived. The rate ${1/2}\log(1+\es)$ is shown to be the generalized mutual information of a modified minimum-distance decoder, when the…

Information Theory · Computer Science 2008-09-22 Alfonso Martinez

Given a Poisson process on a bounded interval, its random geometric graph is the graph whose vertices are the points of the Poisson process and edges exist between two points if and only if their distance is less than a fixed given…

Probability · Mathematics 2010-08-31 Laurent Decreusefond , Eduardo Ferraz

We generalize the results on the asymptotic expansion from Gaussian Unitary Ensembles case to all Gaussian Ensembles. We derive differential equations on densities and their moment generating functions for all Gaussian Ensembles. Also, we…

Probability · Mathematics 2018-01-09 Yaroslav Naprienko

We show that the zeros of random sequences of Gaussian systems of polynomials of increasing degree almost surely converge to the expected limit distribution under very general hypotheses. In particular, the normalized distribution of zeros…

Complex Variables · Mathematics 2015-05-13 Bernard Shiffman

We investigate the shape of the spectrum and the spectral fluctuations of the $k$-body Embedded Gaussian Ensemble for Bosons in the dense limit, where the number of Bosons $m \to \infty$ while both $k$, the rank of the interaction, and $l$,…

Condensed Matter · Physics 2011-07-19 T. Asaga , L. Benet , T. Rupp , H. A. Weidenmueller

Compressed sensing is a new scheme which shows the ability to recover sparse signal from fewer measurements, using $l_1$ minimization. Recently, Chartrand and Staneva shown in \cite{CS1} that the $l_p$ minimization with $0<p<1$ recovers…

Functional Analysis · Mathematics 2011-03-02 Yi Shen , Song Li

We study the stability of the mesoscopic fluctuations of certain orthogonal polynomial ensembles on the real line utilizing the recurrence relation of the associated orthogonal polynomials. We prove that under a sparse enough decaying…

Mathematical Physics · Physics 2024-10-11 Daniel Ofner

The present article derives the minimal number $N$ of observations needed to consider a Bayesian posterior distribution as Gaussian. Two examples are presented. Within one of them, a chi-squared distribution, the observable $x$ as well as…

Statistics Theory · Mathematics 2020-12-03 Christoph Fuhrmann , Hanns Ludwig Harney , Klaus Harney , Andreas Müller

In this manuscript we introduce and study an extended version of the minimal dispersion of point sets, which has recently attracted considerable attention. Given a set $\mathscr P_n=\{x_1,\dots,x_n\}\subset [0,1]^d$ and…

Numerical Analysis · Mathematics 2019-08-15 Aicke Hinrichs , Joscha Prochno , Mario Ullrich , Jan Vybiral

Modelling the chaotic states in terms of the Gaussian Orthogonal Ensemble of random matrices (GOE), we investigate the interaction of the GOE with regular bound states. The eigenvalues of the latter may or may not be embedded in the GOE…

Nuclear Theory · Physics 2008-11-26 A. De Pace , A. Molinari , H. A. Weidenmueller

Linear combinations of translations of a single Gaussian, e^{-x^2}, are shown to be dense in L^2(R). Two algorithms for determining the coefficients for the approximations are given, using orthogonal Hermite functions and least squares.…

Classical Analysis and ODEs · Mathematics 2008-05-27 Craig Calcaterra , Axel Boldt

We consider locally isotropic Gaussian random fields on the $N$-dimensional Euclidean space for fixed $N$. Using the so called Gaussian Orthogonally Invariant matrices first studied by Mallows in 1961 which include the celebrated Gaussian…

Probability · Mathematics 2024-01-31 Hao Xu , Haoran Yang , Qiang Zeng

The Gaussian theory of errors has been generalized to situations, where the Gaussian distribution and, hence, the Gaussian rules of error propagation are inadequate. The generalizations are based on Bayes' theorem and a suitable measure.…

Data Analysis, Statistics and Probability · Physics 2007-05-23 Hanns L. Harney