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Related papers: Gaussian Multiplicative Chaos for i.i.d. matrices

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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

By formulating the inverse problem of partial differential equations (PDEs) as a statistical inference problem, the Bayesian approach provides a general framework for quantifying uncertainties. In the inverse problem of PDEs, parameters are…

Numerical Analysis · Mathematics 2026-02-10 Haoyu Lu , Junxiong Jia , Deyu Meng

A matrix $A\in\mathbb{C}^{n\times n}$ is diagonalizable if it has a basis of linearly independent eigenvectors. Since the set of nondiagonalizable matrices has measure zero, every $A\in \mathbb{C}^{n\times n}$ is the limit of diagonalizable…

Functional Analysis · Mathematics 2020-04-23 Jess Banks , Archit Kulkarni , Satyaki Mukherjee , Nikhil Srivastava

We study the fluctuations of eigenvalues from a class of Wigner random matrices that generalize the Gaussian orthogonal ensemble. We begin by considering an $n \times n$ matrix from the Gaussian orthogonal ensemble (GOE) or Gaussian…

Probability · Mathematics 2011-03-03 Sean O'Rourke

The classical mixture of Gaussians model is related to K-means via small-variance asymptotics: as the covariances of the Gaussians tend to zero, the negative log-likelihood of the mixture of Gaussians model approaches the K-means objective,…

Machine Learning · Statistics 2013-02-19 Tamara Broderick , Brian Kulis , Michael I. Jordan

In this paper, we study the singularly perturbed Gaussian unitary ensembles defined by the measure \begin{equation*} \frac{1}{C_n} e^{- n\textrm{tr}\, V(M;\lambda,\vec{t}\;)}dM, \end{equation*} over the space of $n \times n$ Hermitian…

Mathematical Physics · Physics 2019-10-23 Dan Dai , Shuai-Xia Xu , Lun Zhang

Consider the product $X = X_{1}\cdots X_{m}$ of $m$ independent $n\times n$ iid random matrices. When $m$ is fixed and the dimension $n$ tends to infinity, we prove Gaussian limits for the centered linear spectral statistics of $X$ for…

Probability · Mathematics 2019-04-11 Natalie Coston , Sean O'Rourke

The eigenvalues of quantum chaotic systems have been conjectured to follow, in the large energy limit, the statistical distribution of eigenvalues of random ensembles of matrices of size $N\rightarrow\infty$. Here we provide semiclassical…

Chaotic Dynamics · Physics 2011-12-07 P. Leboeuf , A. G. Monastra

For random matrix ensembles with non-gaussian matrix elements that may exhibit some correlations, it is shown that centered traces of polynomials in the matrix converge in distribution to a Gaussian process whose covariance matrix is…

Mathematical Physics · Physics 2009-04-24 Jeffrey Schenker , Hermann Schulz-Baldes

In this article we systematically study the general properties and the single-point moments of the inverse of the Gaussian multiplicative chaos.

Probability · Mathematics 2024-05-30 Ilia Binder , Tomas Kojar

Let $S_n=\frac{1}{n}X_nX_n^*$ where $X_n=\{X_{ij}\}$ is a $p\times n$ matrix with i.i.d. complex standardized entries having finite fourth moments. Let $Y_n(\mathbf {t}_1,\mathbf {t}_2,\sigma)=\sqrt{p}({\mathbf {x}}_n(\mathbf…

Probability · Mathematics 2012-01-04 Z. D. Bai , H. X. Liu , W. K. Wong

We focus on the FeigenbaumCoulletTresser point of the dissipative one-dimensional z logistic map. We show that sums of iterates converge to q Gaussian distributions, which optimize the nonadditive entropic functional Sq under simple…

Statistical Mechanics · Physics 2025-08-20 Abbas Ali Saberi , Ugur Tirnakli , Constantino Tsallis

In this article, we extend the theory of multiplicative chaos for positive definite functions in Rd of the form f(x) = 2 ln+ T|x|+ g(x) where g is a continuous and bounded function. The construction is simpler and more general than the one…

Probability · Mathematics 2008-07-08 Raoul Robert , Vincent Vargas

For a given normalized Gaussian symmetric matrix-valued process $Y^{(n)}$, we consider the process of its eigenvalues $\{(\lambda_{1}^{(n)}(t),\dots, \lambda_{n}^{(n)}(t)); t\ge 0\}$ as well as its corresponding process of empirical…

Probability · Mathematics 2018-01-09 Arturo Jaramillo , Juan Carlos Pardo , José Luis Pérez

We study the high-frequency Fourier asymptotics of imaginary Gaussian multiplicative chaos on the unit circle, a complex-valued random distribution formally given by $\mathrm M_{\mathrm i\beta}=\exp(\mathrm i\beta X)$, where $X$ is a…

Probability · Mathematics 2026-05-13 Benjamin Bonnefont , Hermanni Rajamäki , Vincent Vargas

Motivated by isotropic fully developed turbulence, we define a theory of symmetric matrix valued isotropic Gaussian multiplicative chaos. Our construction extends the scalar theory developed by J.P. Kahane in 1985.

Probability · Mathematics 2015-06-05 Laurent Chevillard , Rémi Rhodes , Vincent Vargas

We consider $N\times N$ symmetric random matrices where the probability distribution for each matrix element is given by a measure $\nu$ with a subexponential decay. We prove that the eigenvalue spacing statistics in the bulk of the…

Mathematical Physics · Physics 2010-11-25 Laszlo Erdos , Benjamin Schlein , Horng-Tzer Yau

In this paper, we prove the Fourth Moment Theorem for sequences of (noncommutative) random variables given as sums of two stochastic integrals in two different parity orders of chaos, both in the free Wigner chaos setting and a $q$-Gaussian…

Probability · Mathematics 2025-11-27 Todd Kemp , Akihiro Miyagawa

We propose a measure, which we call the dissipative spectral form factor (DSFF), to characterize the spectral statistics of non-Hermitian (and non-Unitary) matrices. We show that DSFF successfully diagnoses dissipative quantum chaos, and…

Statistical Mechanics · Physics 2021-11-03 Jiachen Li , Tomaž Prosen , Amos Chan

Denote by $\mu_\beta="\exp(\beta X)"$ the Gaussian multiplicative chaos which is defined using a log-correlated Gaussian field $X$ on a domain $U\subset\mathbb{R}^d$. The case $\beta\in\mathbb{R}$ has been studied quite intensively, and…

Probability · Mathematics 2019-05-30 Janne Junnila , Eero Saksman , Lauri Viitasaari
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