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We consider ensembles of real symmetric band matrices with entries drawn from an infinite sequence of exchangeable random variables, as far as the symmetry of the matrices permits. In general the entries of the upper triangular parts of…

Probability · Mathematics 2020-01-22 Werner Kirsch , Thomas Kriecherbauer

We consider an ensemble of large non-Hermitian random matrices of the form $\hat{H}+i\hat{A}_s$, where $\hat{H}$ and $\hat{A}_s$ are Hermitian statistically independent random $N\times N$ matrices. We demonstrate the existence of a new…

Condensed Matter · Physics 2016-08-31 Yan V. Fyodorov , Boris A. Khoruzhenko , Hans-Juergen Sommers

For each $n$, let $A_n=(\sigma_{ij})$ be an $n\times n$ deterministic matrix and let $X_n=(X_{ij})$ be an $n\times n$ random matrix with i.i.d. centered entries of unit variance. In the companion article Cook et al., we considered the…

Probability · Mathematics 2020-07-31 Nicholas A. Cook , Walid Hachem , Jamal Najim , David Renfrew

The density of complex eigenvalues of random asymmetric $N\times N$ matrices is found in the large-$N$ limit. The matrices are of the form $H_0+A$ where $A$ is a matrix of $N^2$ independent, identically distributed random variables with…

Condensed Matter · Physics 2009-10-28 Boris A Khoruzhenko

We show that the limiting minimal eigenvalue distributions for a natural generalization of Gaussian sample-covariance structures (the "beta ensembles") are described by the spectrum of a random diffusion generator. By a Riccati…

Probability · Mathematics 2009-11-13 Jose A. Ramirez , Brian Rider

We consider random matrices whose entries are f(<Xi,Xj>) or f(||Xi-Xj||^2) for iid vectors Xi in R^p with normalized distribution. Assuming that f is sufficiently smooth and the distribution of Xi's is sufficiently nice, El Karoui [17]…

Probability · Mathematics 2013-05-22 Yen Do , Van Vu

We study the special case of $n\times n$ 1D Gaussian Hermitian random band matrices, when the covariance of the elements is determined by the matrix $J=(-W^2\triangle+1)^{-1}$. Assuming that $n\ge CW\log W\gg 1$, we prove that the averaged…

Mathematical Physics · Physics 2016-08-24 Mariya Shcherbina , Tatyana Shcherbina

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 the asymptotic local behavior of the second correlation functions of the characteristic polynomials of a certain class of Gaussian $N\times N$ non-Hermitian random band matrices with a bandwidth $W$. Given $W,N\to\infty$, we…

Mathematical Physics · Physics 2025-10-13 Mariya Shcherbina , Tatyana Shcherbina

In mathematical models of epidemic diffusion on networks based upon systems of differential equations, it is convenient to use the Heterogeneous Mean Field approximation (HMF) because it allows to write one single equation for all nodes of…

Physics and Society · Physics 2024-11-12 L. Di Lucchio , G. Modanese

We study the special case of $n\times n$ 1D Gaussian Hermitian random band matrices, when the covariance of the elements is determined by $J=(-W^2\triangle+1)^{-1}$. Assuming that the band width $W\ll \sqrt{n}$, we prove that the limit of…

Mathematical Physics · Physics 2017-04-05 Mariya Shcherbina , Tatyana Shcherbina

We study the statistics of eigenvectors in correlated random band matrix models. These models are characterized by two parameters, the band width B(N) of a Hermitian N times N matrix and the correlation parameter C(N) describing…

Mesoscale and Nanoscale Physics · Physics 2009-10-31 Martin Janssen , Krystian Pracz

Understanding the distributions of spectral estimators in low-rank random matrix models, also known as signal-plus-noise matrix models, is fundamentally important in various statistical learning problems, including network analysis, matrix…

Statistics Theory · Mathematics 2024-03-15 Fangzheng Xie , Yichi Zhang

In this work we examine the dispersion of conservative tracers (bromide and fluorescein) in an experimentally-constructed three-dimensional dual-porosity porous medium. The medium is highly heterogeneous ($\sigma_Y^2=5.7$), and consists of…

Fluid Dynamics · Physics 2018-03-14 Daniel Vogler , Sassan Ostvar , Rebecca Paustian , Brian Wood

We study the local eigenvalue statistics $\xi_{\omega,E}^N$ associated with the eigenvalues of one-dimensional, $(2N+1) \times (2N+1)$ random band matrices with independent, identically distributed, real random variables and band width…

Mathematical Physics · Physics 2022-05-04 Peter D. Hislop , M. Krishna

We consider $N\times N$ Hermitian random matrices with independent identically distributed entries (Wigner matrices). We assume that the distribution of the entries have a Gaussian component with variance $N^{-3/4+\beta}$ for some positive…

Mathematical Physics · Physics 2010-04-05 Laszlo Erdos , Jose A. Ramirez , Benjamin Schlein , Horng-Tzer Yau

We analyze the propagation properties of the numerical versions of one and two-dimensional wave equations, semi-discretized in space by finite difference schemes. We focus on high-frequency solutions whose propagation can be described, both…

Analysis of PDEs · Mathematics 2018-06-26 Umberto Biccari , Aurora Marica , Enrique Zuazua

We study eigenvectors in the deformed Gaussian unitary ensemble of random matrices $H=W\tilde{H}W$, where $\tilde{H}$ is a random matrix from Gaussian unitary ensemble and $W$ is a deterministic diagonal matrix with positive entries. Using…

Mathematical Physics · Physics 2017-01-12 Kevin Truong , Alexander Ossipov

It is a classical result of Wigner that for an hermitian matrix with independent entries on and above the diagonal, the mean empirical eigenvalue distribution converges weakly to the semicircle law as matrix size tends to infinity. In this…

Probability · Mathematics 2007-07-17 Katrin Hofmann-Credner , Michael Stolz

Score-based diffusion models have achieved remarkable empirical success in generating high-quality samples from target data distributions. Among them, the Denoising Diffusion Probabilistic Model (DDPM) is one of the most widely used…

Machine Learning · Statistics 2025-12-16 Yuchen Jiao , Yuchen Zhou , Gen Li