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We prove a variant of the central limit theorem (CLT) for a sequence of i.i.d. random variables $\xi_j$, perturbed by a stochastic sequence of linear transformations $A_j$, representing the model uncertainty. The limit, corresponding to a…

Probability · Mathematics 2015-07-20 Dmitry B. Rokhlin

We continue investigations of our previous papers, in which there were proved central limit theorems (CLT) for linear eigenvalue statistics Tr f(M_n) and there were found the limiting probability laws for the normalised matrix elements of…

Mathematical Physics · Physics 2012-01-17 Anna Lytova

Let $(\tau_n)$ be a sequence of toral automorphisms $\tau_n : x \rightarrow A_n x \hbox{mod}\ZZ^d$ with $A_n \in {\cal A}$, where ${\cal A}$ is a finite set of matrices in $SL(d, \mathbb{Z})$. Under some conditions the method of…

Probability · Mathematics 2010-06-22 Jean-Pierre Conze , Stéphane Le Borgne , Mikaël Roger

The scaled standard Wigner matrix (symmetric with mean zero, variance one i.i.d. entries), and its limiting eigenvalue distribution, namely the semi-circular distribution, has attracted much attention. The $2k$th moment of the limit equals…

Probability · Mathematics 2021-03-18 Arup Bose , Koushik Saha , Arusharka Sen , Priyanka Sen

We consider Betti numbers of the excursion of a smooth Euclidean Gaussian field restricted to a rectangular window, in the asymptotics where the window grows to R^d . With motivations coming from Topological Data Analysis, we derive a…

Probability · Mathematics 2025-12-16 Christian Hirsch , Raphaël Lachièze-Rey

For large dimensional non-Hermitian random matrices $X$ with real or complex independent, identically distributed, centered entries, we consider the fluctuations of $f(X)$ as a matrix where $f$ is an analytic function around the spectrum of…

Probability · Mathematics 2021-12-22 László Erdős , Hong Chang Ji

The theory of random matrices contains many central limit theorems. We have central limit theorems for eigenvalues statistics, for the log-determinant and log-permanent, for limiting distribution of individual eigenvalues in the bulk, and…

Probability · Mathematics 2016-05-25 Asaf Ferber , Daniel Montealegre , Van Vu

We show that if a permutation statistic can be written as a linear combination of bivincular patterns, then its moments can be expressed as a linear combination of factorials with constant coefficients. This generalizes a result of…

Combinatorics · Mathematics 2021-09-21 Stoyan Dimitrov , Niraj Khare

The Central Limit Theorem (CLT) for additive functionals of Markov chains is a well known result with a long history. In this paper we present applications to two finite-memory versions of the Elephant Random Walk, solving a problem from…

Probability · Mathematics 2020-05-04 Iddo Ben-Ari , Jonah Green , Taylor Meredith , Hugo Panzo , Xiaoran Tan

We prove central limit theorems (CLTs) for topological functionals of Bernoulli bond percolation on infinite graphs beyond the Euclidean lattice $\mathbb{Z}^{d}$. For quasi-transitive graphs of subexponential growth, we show that the number…

Probability · Mathematics 2026-04-10 Luciano H. L. de Araújo , Daniel Miranda Machado , Cristian F. Coletti

In the present paper, we study central limit theorems (CLTs) for non-symmetric random walks on nilpotent covering graphs from a point of view of discrete geometric analysis developed by Kotani and Sunada. We establish a semigroup CLT for a…

Probability · Mathematics 2021-08-17 Satoshi Ishiwata , Hiroshi Kawabi , Ryuya Namba

We consider sequences of symmetric $U$-statistics, not necessarily Hoeffding-degenerate, both in a one- and multi-dimensional setting, and prove quantitative central limit theorems (CLTs) based on the use of {\it contraction operators}. Our…

Probability · Mathematics 2021-04-01 Christian Döbler , Giovanni Peccati

We establish a central limit theorem for the eigenvalue counting function of a matrix of real Gaussian random variables.

Probability · Mathematics 2024-03-12 Advay Goel , Patrick Lopatto , Xiaoyu Xie

We extend the spectral method for proving limit theorems to random non-uniformly expanding dynamical systems. This yields the CLT and moderate deviations principles (MDP). We show that as the amount of non-uniformity decreases the CLT rates…

Dynamical Systems · Mathematics 2024-08-14 Yeor Hafouta

Random Matrix Theory (RMT) has successfully modeled diverse systems, from energy levels of heavy nuclei to zeros of $L$-functions. Many statistics in one can be interpreted in terms of quantities of the other; for example, zeros of…

The theory of Generalized Locally Toeplitz (GLT) sequences of matrices has been developed in order to study the asymptotic behaviour of particular spectral distributions when the dimension of the matrices tends to infinity. A key concepts…

Numerical Analysis · Mathematics 2021-02-04 Giovanni Barbarino

In the paper [25], written in collaboration with Gesine Reinert, we proved a universality principle for the Gaussian Wiener chaos. In the present work, we aim at providing an original example of application of this principle in the…

Probability · Mathematics 2010-02-08 Ivan Nourdin , Giovanni Peccati

We prove the Central Limit Theorem (CLT) from the definition of weak convergence using the Haar wavelet basis, calculus, and elementary probability. The use of the Haar basis pinpoints the role of $L^{2}([0,1])$ in the CLT as well as the…

Probability · Mathematics 2015-10-29 Vladimir Dobric , Patricia Garmirian

Previous results indicate that while chaos can lead to substantial entropy production, thereby maximizing dynamical entanglement, this still falls short of maximality. Random Matrix Theory (RMT) modeling of composite quantum systems,…

Quantum Physics · Physics 2009-11-07 Jayendra N. Bandyopadhyay , Arul Lakshminarayan

Fleming-Viot type particle systems represent a classical way to approximate the distribution of a Markov process with killing, given that it is still alive at a final deterministic time. In this context, each particle evolves independently…

Probability · Mathematics 2017-09-21 Bernard Delyon , Frédéric Cérou , Arnaud Guyader , Mathias Rousset
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