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The central limit theorem provides the theoretical foundation for the universality of the normal distribution: under broad conditions, the asymptotic distribution of a sum of independent random variables approaches a Gaussian. Yet, physical…

Data Analysis, Statistics and Probability · Physics 2026-03-26 Mario Castro , José A. Cuesta

In this paper, we initiate the harmonic analysis of Gaussian multiplicative chaos (GMC) on the circle, i.e. the study of its Fourier coefficients. In particular, we show that almost surely GMC is a so-called Rajchman measure which means…

Probability · Mathematics 2024-03-01 Christophe Garban , Vincent Vargas

The goal of this article is to expand on the relationship between random matrix and multiplicative chaos theories using the integrability properties of the circular beta-ensembles. We give a comprehensive proof of the multiplicative chaos…

Probability · Mathematics 2024-07-30 Gaultier Lambert , Joseph Najnudel

Let $A$ be an isotropic, sub-gaussian $m \times n$ matrix. We prove that the process $Z_x := \|Ax\|_2 - \sqrt m \|x\|_2$ has sub-gaussian increments. Using this, we show that for any bounded set $T \subseteq \mathbb{R}^n$, the deviation of…

Probability · Mathematics 2016-06-08 Christopher Liaw , Abbas Mehrabian , Yaniv Plan , Roman Vershynin

Gaussian Quadrature is a well known technique for numerical integration. Recently Gaussian quadrature with respect to discrete measures corresponding to finite sums have found some new interest. In this paper we apply these ideas to…

Numerical Analysis · Mathematics 2007-05-23 Hartmut Monien

We demonstrate the convergence of the characteristic polynomial of several random matrix ensembles to a limiting universal function, at the microscopic scale. The random matrix ensembles we treat are classical compact groups and the…

Probability · Mathematics 2019-02-05 Reda Chhaibi , Emma Hovhannisyan , Joseph Najnudel , Ashkan Nikeghbali , Brad Rodgers

We construct the analogue of Gaussian multiplicative chaos measures for the local times of planar Brownian motion by exponentiating the square root of the local times of small circles. We also consider a flat measure supported on points…

Probability · Mathematics 2022-11-10 Antoine Jego

We prove that under fairly general conditions properly rescaled determinantal random point field converges to a generalized Gaussian random process.

Probability · Mathematics 2007-05-23 Alexander Soshnikov

We prove mixing convergence of the least squares estimator of autoregressive parameters for supercritical autoregressive processes of order 2 with Gaussian innovations having real characteristic roots with different absolute values. We use…

Statistics Theory · Mathematics 2025-09-16 Matyas Barczy , Fanni Nedényi , Gyula Pap

Given a measure $\nu$ on a regular planar domain $D$, the Gaussian multiplicative chaos measure of $\nu$ studied in this paper is the random measure ${\widetilde \nu}$ obtained as the limit of the exponential of the $\gamma$-parameter…

Probability · Mathematics 2018-12-14 Kenneth Falconer , Xiong Jin

For $f$ a Steinhaus random multiplicative function, we prove convergence in distribution of the appropriately normalised partial sums \[ \frac{{(\log \log x)}^{1/4}}{\sqrt{x}} \sum_{\substack{n \leq x \\ P(n) > \sqrt{x}}} f(n), \] where…

Number Theory · Mathematics 2025-03-11 Seth Hardy

The Gauss map (or continued fraction map) is an important dissipative one-dimensional discrete-time dynamical system that exhibits chaotic behaviour and which generates a symbolic dynamics consisting of infinitely many different symbols.…

Statistical Mechanics · Physics 2025-08-11 Christian Beck , Ugur Tirnakli , Constantino Tsallis

The present note is an essential addition to the author's arxiv paper arXiv:2001.01070, concerning general multiplicative systems of random variables. Using some lemmas and the methodology of \cite{Kar4}, we obtain a general extreme…

Probability · Mathematics 2025-12-09 Grigori A. Karagulyan

In this paper, we propose a data based transformation for infinite-dimensional Gaussian processes and derive its limit theorem. For a classification problem, this transformation induces complete separation among the associated Gaussian…

Statistics Theory · Mathematics 2022-03-25 Juan A. Cuesta-Albertos , Subhajit Dutta

We generalize Huberman-Rudnick universal scaling law for all periodic windows of the logistic map and show the robustness of $q$-Gaussian probability distributions in the vicinity of chaos threshold. Our scaling relation is universal for…

Chaotic Dynamics · Physics 2015-06-12 Ozgur Afsar , Ugur Tirnakli

Quadratic variations of Gaussian processes play important role in both stochastic analysis and in applications such as estimation of model parameters, and for this reason the topic has been extensively studied in the literature. In this…

Probability · Mathematics 2015-02-06 Lauri Viitasaari

This paper explores certain kinds of empirical process with respect to the components of multivariate Gaussian. We put forward some finite sample bounds which hold for multivariate Gaussian under general dependence. We give necessary and…

Probability · Mathematics 2020-07-03 Jikai Hou

We introduce a unified approach for studying the polynomial Fourier decay of classical multiplicative chaos measures. As consequences, we obtain the precise Fourier dimensions for multiplicative chaos measures arising from the following key…

Probability · Mathematics 2025-06-18 Zhaofeng Lin , Yanqi Qiu , Mingjie Tan

We prove multi-dimensional central limit theorems for the spectral moments (of arbitrary degrees) associated with random matrices with real-valued i.i.d. entries, satisfying some appropriate moment conditions. Our techniques rely on a…

Probability · Mathematics 2009-09-30 Ivan Nourdin , Giovanni Peccati

We compute explicit bounds in the normal and chi-square approximations of multilinear homogenous sums (of arbitrary order) of general centered independent random variables with unit variance. In particular, we show that chaotic random…

Probability · Mathematics 2010-11-08 Ivan Nourdin , Giovanni Peccati , Gesine Reinert