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Unlike an irreducible $Z$-matrices, a weakly irreducible $Z$-tensor $\mathcal{A}$ can have more than one eigenvector associated with the least H-eigenvalue. We show that there are finitely many eigenvectors of $\mathcal{A}$ associated with…

Combinatorics · Mathematics 2019-01-25 Yi-Zheng Fan , Yi Wang , Yan-Hong Bao

The tail behavior of aggregates of heavy-tailed random vectors is known to be determined by the so-called principle of "one large jump'', be it for finite sums, random sums, or, L\'evy processes. We establish that, in fact, a more general…

Probability · Mathematics 2023-01-26 Bikramjit Das , Vicky Fasen-Hartmann

We explore the spectral properties of the $4$-fermion Sachdev-Ye-Kitaev model with interaction sourced from a L\'evy Stable (fat-tailed) distribution. L\'evy random matrices are known to demonstrate non-ergodic behaviour through the…

Quantum Physics · Physics 2025-06-06 Budhaditya Bhattacharjee , William E. Salazar , Dario Rosa , Alexei Andreanov

We consider the local statistics of $H = V^* X V + U^* Y U$ where $V$ and $U$ are independent Haar-distributed unitary matrices, and $X$ and $Y$ are deterministic real diagonal matrices. In the bulk, we prove that the gap statistics and…

Probability · Mathematics 2017-01-04 Ziliang Che , Benjamin Landon

We study the eigenvalues and the eigenvectors of $N\times N$ structured random matrices of the form $H = W\tilde{H}W+D$ with diagonal matrices $D$ and $W$ and $\tilde{H}$ from the Gaussian Unitary Ensemble. Using the supersymmetry technique…

Mathematical Physics · Physics 2018-08-20 Kevin Truong , Alexander Ossipov

We study the asymptotic distributions of the spiked eigenvalues and the largest nonspiked eigenvalue of the sample covariance matrix under a general covariance matrix model with divergent spiked eigenvalues, while the other eigenvalues are…

Statistics Theory · Mathematics 2017-11-07 Tony Cai , Xiao Han , Guangming Pan

We calculate analytically the probability of large deviations from its mean of the largest (smallest) eigenvalue of random matrices belonging to the Gaussian orthogonal, unitary and symplectic ensembles. In particular, we show that the…

Statistical Mechanics · Physics 2009-11-11 David S. Dean , Satya N. Majumdar

We show central limit theorems (CLT) for the Stieltjes transforms or more general analytic functions of symmetric matrices with independent heavy tailed entries, including entries in the domain of attraction of $\alpha$-stable laws and…

Probability · Mathematics 2015-06-12 Florent Benaych-Georges , Alice Guionnet , Camille Male

Heavy-tailed fluctuations and power law statistics pervade physics, finance, and economics, yet their origin is often ascribed to systems poised near criticality. Here we show that such behavior can emerge far from instability through a…

Statistical Mechanics · Physics 2025-10-15 Virgile Troude , Didier Sornette

The eigenvalue density for members of the Gaussian orthogonal and unitary ensembles follows the Wigner semi-circle law. If the Gaussian entries are all shifted by a constant amount c/Sqrt(2N), where N is the size of the matrix, in the large…

Mathematical Physics · Physics 2009-04-21 Kevin E. Bassler , Peter J. Forrester , Norman E. Frankel

We consider the eigenvalues of sample covariance matrices of the form $\mathcal{Q}=(\Sigma^{1/2}X)(\Sigma^{1/2}X)^*$. The sample $X$ is an $M\times N$ rectangular random matrix with real independent entries and the population covariance…

Probability · Mathematics 2020-09-16 Jinwoong Kwak , Ji Oon Lee , Jaewhi Park

In this paper, we investigate the spectral properties of the adjacency and the Laplacian matrices of random graphs. We prove that: (i) the law of large numbers for the spectral norms and the largest eigenvalues of the adjacency and the…

Probability · Mathematics 2010-11-12 Xue Ding , Tiefeng Jiang

Consider an n x n Hermitian random matrix with, above the diagonal, independent entries with alpha-stable symmetric distribution and 0 < alpha < 2. We establish new bounds on the rate of convergence of the empirical spectral distribution of…

Probability · Mathematics 2012-02-01 Charles Bordenave , Alice Guionnet

We consider a class of sparse random matrices, which includes the adjacency matrix of Erd\H{o}s-R\'enyi graphs $\mathcal G(N,p)$ for $p \in [N^{\varepsilon-1},N^{-\varepsilon}]$. We identify the joint limiting distributions of the…

Probability · Mathematics 2020-03-13 Yukun He

We consider the eigenvalues and eigenvectors of finite, low rank perturbations of random matrices. Specifically, we prove almost sure convergence of the extreme eigenvalues and appropriate projections of the corresponding eigenvectors of…

Probability · Mathematics 2012-03-19 Florent Benaych-Georges , Raj Rao Nadakuditi

In this paper we study the joint distributional convergence of the largest eigenvalues of the sample covariance matrix of a $p$-dimensional time series with iid entries when $p$ converges to infinity together with the sample size $n$. We…

Probability · Mathematics 2016-08-26 Johannes Heiny , Thomas Mikosch

We consider Erd\H{o}s-R\'enyi-type random hypergraphs that are non-uniform, in the sense that hyperedges of different sizes may coexist, and inhomogeneous, in that connection probabilities may depend on the hyperedge size. All parameters…

Probability · Mathematics 2026-04-03 Luca Avena , Elia Bisi , Eleonora Bordiga

We examine the empirical distribution of the eigenvalues and the eigenvectors of adjacency matrices of sparse regular random graphs. We find that when the degree sequence of the graph slowly increases to infinity with the number of…

Probability · Mathematics 2012-10-15 Ioana Dumitriu , Soumik Pal

We study large Wigner random matrices in the case when the marginal distributions of matrix entries have heavy tails. We prove that the largest eigenvalues of such matrices have Poisson statistics.

Probability · Mathematics 2007-05-23 Alexander Soshnikov

The current work applies some recent combinatorial tools due to Jain to control the eigenvalue gaps of a matrix $M_n = M + N_n$ where $M$ is deterministic, symmetric with large operator norm and $N_n$ is a random symmetric matrix with…

Probability · Mathematics 2022-11-02 Kyle Luh , Ryan Vogel , Alan Yu
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