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Previous literature on random matrix and network science has traditionally employed measures derived from nearest-neighbor level spacing distributions to characterize the eigenvalue statistics of random matrices. This approach, however,…

Disordered Systems and Neural Networks · Physics 2021-01-04 Thomas Peron , Bruno Messias F. de Resende , Francisco A. Rodrigues , Luciano da F. Costa , J. A. Méndez-Bermúdez

We study the statistical and dynamic properties of the systems characterized by an ultrametric space of states and translationary non-invariant symmetric transition matrices of the Parisi type subjected to "locally constant" randomization.…

Disordered Systems and Neural Networks · Physics 2009-11-13 V. A. Avetisov , A. Kh. Bikulov , S. K. Nechaev

A connection between integrability properties and general statistical properties of the spectra of symmetric transfer matrices of the asymmetric eight-vertex model is studied using random matrix theory (eigenvalue spacing distribution and…

Condensed Matter · Physics 2009-10-28 H. Meyer , J. -C. Anglès d'Auriac , J. -M. Maillard

We study the large-deviation properties of minimum spanning trees for two ensembles of random graphs with $N$ nodes. First, we consider complete graphs. Second, we study Erd\H{o}s-R\'{e}nyi (ER) random graphs with edge probability $p=c/N$…

Disordered Systems and Neural Networks · Physics 2025-12-16 Mahdi Sarikhani , Alexander K. Hartmann

A non-Hermitean extension of paradigmatic Wishart random matrices is introduced to set up a theoretical framework for statistical analysis of (real, complex and real quaternion) stochastic time series representing two "remote" complex…

Mathematical Physics · Physics 2011-02-07 Eugene Kanzieper , Navinder Singh

The nearest-neighbor level-spacing distributions are a fundamental quantity of disordered systems and universal. It is well-known that extended and localized states of random Hermitian systems follow the Wigner-Dyson and the Poison…

Disordered Systems and Neural Networks · Physics 2022-08-23 C. Wang , X. R. Wang

We consider the real eigenvalues of an $(N \times N)$ real elliptic Ginibre matrix whose entries are correlated through a non-Hermiticity parameter $\tau_N\in [0,1]$. In the almost-Hermitian regime where $1-\tau_N=\Theta(N^{-1})$, we obtain…

Probability · Mathematics 2022-03-22 Sung-Soo Byun , Nam-Gyu Kang , Ji Oon Lee , Jinyeop Lee

We consider random Hermitian matrices with independent upper triangular entries. Wigner's semicircle law says that under certain additional assumptions, the empirical spectral distribution converges to the semicircle distribution. We…

Probability · Mathematics 2022-06-14 Calvin Wooyoung Chin

Singular-value statistics (SVS) has been recently presented as a random matrix theory tool able to properly characterize non-Hermitian random matrix ensembles [PRX Quantum {\bf 4}, 040312 (2023)]. Here, we perform a numerical study of the…

Applications · Statistics 2024-04-30 J. A. Mendez-Bermudez , R. Aguilar-Sanchez

We introduce a random matrix model where the entries are dependent across both rows and columns. More precisely, we investigate matrices of the form $\X=(X_{(i-1)n+t})_{it}\in\R^{p\times n}$ derived from a linear process $X_t=\sum_j c_j…

Probability · Mathematics 2012-02-15 Oliver Pfaffel , Eckhard Schlemm

We consider two $n\times n$ non-Hermitian random matrices such that the $ij$th entry of one matrix is correlated with the $ij$th entry of the other matrix. However, the entries of any particular matrix are i.i.d. random variables. We study…

Probability · Mathematics 2025-04-08 Indrajit Jana , Sunita Rani

We consider a Wigner-type ensemble, i.e. large hermitian $N\times N$ random matrices $H=H^*$ with centered independent entries and with a general matrix of variances $S_{xy}=\mathbb E|H_{xy}|^2$. The norm of $H$ is asymptotically given by…

Probability · Mathematics 2018-02-15 László Erdős , Peter Mühlbacher

We discuss the limiting spectral density of real symmetric random matrices. Other than in standard random matrix theory the upper diagonal entries are not assumed to be independent, but we will fill them with the entries of a stochastic…

Probability · Mathematics 2015-12-09 Matthias Löwe , Kristina Schubert

The random variable $1+z_1+z_1z_2+\dots$ appears in many contexts and was shown by Kesten to exhibit a heavy tail distribution. We consider natural extensions of this variable and its associated recursion to $N \times N$ matrices either…

Statistical Mechanics · Physics 2021-08-03 Tristan Gautié , Jean-Philippe Bouchaud , Pierre Le Doussal

We equip the polytope of $n\times n$ Markov matrices with the normalized trace of the Lebesgue measure of $\mathbb{R}^{n^2}$. This probability space provides random Markov matrices, with i.i.d. rows following the Dirichlet distribution of…

Probability · Mathematics 2010-06-16 Djalil Chafai

In this note, we give a precise description of the limiting empirical spectral distribution (ESD) for the non-backtracking matrices for an Erd\H{o}s-R\'{e}nyi graph assuming $np/\log n$ tends to infinity. We show that derandomizing part of…

Probability · Mathematics 2024-01-01 Ke Wang , Philip Matchett Wood

We develop a unified approach to bounding the largest and smallest singular values of an inhomogeneous random rectangular matrix, based on the non-backtracking operator and the Ihara-Bass formula for general random Hermitian matrices with a…

Probability · Mathematics 2024-12-13 Ioana Dumitriu , Yizhe Zhu

We consider the ensemble of N-dimensional random symmetric matrices A that have, in average, p non-zero elements per row. We study the asymptotic behavior of the norm of A in the limit of infinitely increasing N and p. We prove that the…

Probability · Mathematics 2014-11-18 A. Khorunzhy

In this article, we study high-dimensional behavior of empirical spectral distributions $\{L_N(t), t\in[0,T]\}$ for a class of $N\times N$ symmetric/Hermitian random matrices, whose entries are generated from the solution of stochastic…

Probability · Mathematics 2020-08-12 Jian Song , Jianfeng Yao , Wangjun Yuan

We study heavy-tailed Hermitian random matrices that are unitarily invariant. The invariance implies that the eigenvalue and eigenvector statistics are decoupled. The motivating question has been whether a freely stable random matrix has…

Mathematical Physics · Physics 2021-09-27 Mario Kieburg , Adam Monteleone
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