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Classical works of Kac, Salem and Zygmund, and Erd\H{o}s and G\'{a}l have shown that lacunary trigonometric sums despite their dependency structure behave in various ways like sums of independent and identically distributed random…

Probability · Mathematics 2023-12-15 Joscha Prochno , Marta Strzelecka

In an earlier paper the authors proved that limits of convergent graph sequences can be described by various structures, including certain 2-variable real functions called graphons, random graph models satisfying certain consistency…

Combinatorics · Mathematics 2009-02-10 László Lovász , Balázs Szegedy

We present some applications of central limit theorems on mesoscopic scales for random matrices. When combined with the recent theory of "homogenization" for Dyson Brownian Motion, this yields the universality of quantities which depend on…

Probability · Mathematics 2019-11-28 Benjamin Landon , Philippe Sosoe

The dynamics of a one-dimensional stochastic model is studied in presence of an absorbing boundary. The distribution of fluctuations is analytically characterized within the generalized van Kampen expansion, accounting for higher order…

Statistical Mechanics · Physics 2015-05-28 Claudia Cianci , Francesca Di Patti , Duccio Fanelli

This paper introduces the Gaussian multi-Graphical Model, a model to construct sparse graph representations of matrix- and tensor-variate data. We generalize prior work in this area by simultaneously learning this representation across…

Machine Learning · Statistics 2024-02-28 Bailey Andrew , David Westhead , Luisa Cutillo

The purpose of the present paper is to establish moderate deviation principles for a rather general class of random variables fulfilling certain bounds of the cumulants. We apply a celebrated lemma of the theory of large deviations…

Probability · Mathematics 2012-09-28 Hanna Doering , Peter Eichelsbacher

In this paper, we exploit the theory of dense graph limits to provide a new framework to study the stability of graph partitioning methods, which we call structural consistency. Both stability under perturbation as well as asymptotic…

Combinatorics · Mathematics 2016-08-15 Peter Diao , Dominique Guillot , Apoorva Khare , Bala Rajaratnam

We consider the smallest eigenvalues of perturbed Hermitian operators with zero modes, either topological or system specific. To leading order for small generic perturbation we show that the corresponding eigenvalues broaden to a Gaussian…

Statistical Mechanics · Physics 2019-05-15 M. Kieburg , A. Mielke , K. Splittorff

We introduce and study stochastic $N$-particle ensembles which are discretizations for general-$\beta$ log-gases of random matrix theory. The examples include random tilings, families of non-intersecting paths, $(z,w)$-measures, etc. We…

Probability · Mathematics 2017-04-25 Alexei Borodin , Vadim Gorin , Alice Guionnet

We study the fluctuations of smooth linear statistics of Laplace eigenvalues of compact hyperbolic surfaces lying in short energy windows, when averaged over the moduli space of surfaces of a given genus. The average is taken with respect…

Spectral Theory · Mathematics 2023-01-03 Zeév Rudnick , Igor Wigman

Generalised Hermite-Gaussian modes (gHG modes), an extended notion of Hermite-Gaussian modes (HG modes), are formed by the summation of normal HG modes with a characteristic function $\alpha$, which can be used to unite conventional HG…

Optics · Physics 2016-07-20 Yi Wang , Yujie Chen , Yanfeng Zhang , Hui Chen , Siyuan Yu

A central limit theorem is shown for moderately interacting particles in the whole space. The interaction potential approximates singular attractive or repulsive potentials of sub-Coulomb type. It is proved that the fluctuations become…

Probability · Mathematics 2024-05-27 Li Chen , Alexandra Holzinger , Ansgar Jüngel

This work discusses the homogenization analysis for diffusion processes on scale-free metric graphs, using weak variational formulations. The oscillations of the diffusion coefficient along the edges of a metric graph induce internal…

Analysis of PDEs · Mathematics 2016-05-31 Fernando A. Morales , Daniel E. Restrepo

We prove a general normal approximation theorem for local graph statistics in the configuration model, together with an explicit bound on the error in the approximation with respect to the Wasserstein metric. Such statistics take the form…

Probability · Mathematics 2019-03-19 A. D. Barbour , Adrian Röllin

In this paper, we derive the asymptotic distribution of the number of copies of a fixed graph $H$ in a random graph $G_n$ sampled from a sparse graphon model. Specifically, we provide a refined analysis that separates the contributions of…

Fluctuations of observables provide unique insights into the nature of physical systems, and their study stands as a cornerstone of both theoretical and experimental science. Generalized fluctuations, or cumulants, provide information…

Strongly Correlated Electrons · Physics 2025-11-12 Clément Berthière , Benoit Estienne , Jean-Marie Stéphan , William Witczak-Krempa

For partially coherent light fields with random fluctuations, the intensity distributions and statistics have been proven to be more propagation robust compared with coherent light. However, its full potential in practical applications has…

Optics · Physics 2023-03-30 Xingyuan Lu , Zhuoyi Wang , Qiwen Zhan , Yangjian Cai , Chengliang Zhao

Motivated by the task of computing normalizing constants and importance sampling in high dimensions, we study the dimension dependence of fluctuations for additive functionals of time-inhomogeneous Langevin-type diffusions on…

Statistics Theory · Mathematics 2018-09-07 Christophe Andrieu , James Ridgway , Nick Whiteley

In this article, universal concentration estimates are established for the local times of random walks on weighted graphs in terms of the resistance metric. As a particular application of these, a modulus of continuity for local times is…

Probability · Mathematics 2015-06-12 David A. Croydon

We derive normal approximation bounds for generalized $U$-statistics of the form \begin{equation*} S_{n,k}(f):=\sum_{ 1 \leq \beta (1),\dots,\beta (k) \leq n \atop \beta (i)\ne\beta (j), \ 1\leq i\ne j \leq k} f\big(X_{\beta…

Probability · Mathematics 2025-11-12 Qingwei Liu , Nicolas Privault