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We study the probability distribution function $P(\lambda)$ of the largest eigenvalue $\lambda_{\rm max}$ of $N \times N$ random matrices of the form $H + V$, where $H$ belongs to the GOE/GUE ensemble and $V$ is a full rank deterministic…

Statistical Mechanics · Physics 2025-10-14 Pierre Le Doussal

We investigate the emergence of spanning structures in sparse pseudo-random $k$-uniform hypergraphs, using the following comparatively weak notion of pseudo-randomness. A $k$-uniform hypergraph $H$ on $n$ vertices is called…

Combinatorics · Mathematics 2021-08-11 Hiep Hàn , Jie Han , Patrick Morris

Given a large sample covariance matrix $S_N=\frac 1n\Gamma_N^{1/2}Z_N Z_N^*\Gamma_N^{1/2}\, ,$ where $Z_N$ is a $N\times n$ matrix with i.i.d. centered entries, and $\Gamma_N$ is a $N\times N$ deterministic Hermitian positive semidefinite…

Probability · Mathematics 2021-01-08 Florence Merlevède , Jamal Najim , Peng Tian

Two landmark results in combinatorial random matrix theory, due to Koml\'os and Costello-Tao-Vu, show that discrete random matrices and symmetric discrete random matrices are typically nonsingular. In particular, in the language of graph…

Combinatorics · Mathematics 2023-03-10 Margalit Glasgow , Matthew Kwan , Ashwin Sah , Mehtaab Sawhney

We consider random walks in the form of nearest-neighbor hopping on Erdos-Renyi random graphs of finite fixed mean degree c as the number of vertices N tends to infinity. In this regime, using statistical field theory methods, we develop an…

Disordered Systems and Neural Networks · Physics 2025-02-14 Oleg Evnin , Weerawit Horinouchi

In this paper, we consider a data matrix $X\in\mathbb{C}^{N\times M}$ where all the columns are i.i.d. samples being $N$ dimensional complex Gaussian of mean zero and covariance $\Sigma\in\mathbb{C}^{N\times N}$. Here the population matrix…

Probability · Mathematics 2012-07-19 Dai Shi

In this paper, we present a novel approach based on the random walk process for finding meaningful representations of a graph model. Our approach leverages the transient behavior of many short random walks with novel initialization…

Social and Information Networks · Computer Science 2018-05-14 Lin Li , William M. Campbell , Rajmonda S. Caceres

The pattern of zero entries in the inverse covariance matrix of a multivariate normal distribution corresponds to conditional independence restrictions between variables. Covariance selection aims at estimating those structural zeros from…

Statistics Theory · Mathematics 2016-08-16 Nicolai Meinshausen , Peter Bühlmann

We consider three different models of sparse random graphs:~undirected and directed Erd\H{o}s-R\'{e}nyi graphs, and random bipartite graph with an equal number of left and right vertices. For such graphs we show that if the edge…

Probability · Mathematics 2021-02-24 Anirban Basak , Mark Rudelson

We consider a number $\nu_n$ of components in a random graph $G(n,p)$ with $n$ vertices, where the probability of an edge is equal to $p$. By operating with special generating functions we shows the next asymptotic relation for factorial…

Probability · Mathematics 2019-04-03 Nikolay Kazimirow

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 develop a formalism to compute the statistics of the top eigenpair of weighted sparse graphs with finite mean connectivity and bounded maximal degree. Framing the problem in terms of optimisation of a quadratic form on the sphere and…

Statistical Mechanics · Physics 2019-10-28 Vito Antonio Rocco Susca , Pierpaolo Vivo , Reimer Kuehn

We present an algorithm to identify sparse dependence structure in continuous and non-Gaussian probability distributions, given a corresponding set of data. The conditional independence structure of an arbitrary distribution can be…

Machine Learning · Computer Science 2017-11-07 Rebecca E. Morrison , Ricardo Baptista , Youssef Marzouk

We provide a combinatorial characterization of all testable properties of $k$-uniform hypergraphs ($k$-graphs for short). Here, a $k$-graph property $P$ is testable if there is a randomized algorithm which makes a bounded number of edge…

Combinatorics · Mathematics 2025-05-08 Felix Joos , Jaehoon Kim , Daniela Kühn , Deryk Osthus

We investigate the noise sensitivity of the top eigenvector of a sparse random symmetric matrix. Let $v$ be the top eigenvector of an $N\times N$ sparse random symmetric matrix with an average of $d$ non-zero centered entries per row. We…

Probability · Mathematics 2022-04-07 Charles Bordenave , Jaehun Lee

We show by direct calculation that the replica and cavity methods are exactly equivalent for the spectrum of Erdos-Renyi random graph. We introduce a variational formulation based on the cavity method and use it to find approximate…

Statistical Mechanics · Physics 2011-05-26 Frantisek Slanina

We study robust versions of properties of $(n,d,\lambda)$-graphs, namely, the property of a random sparsification of an $(n,d,\lambda)$-graph, where each edge is retained with probability $p$ independently. We prove such results for the…

Combinatorics · Mathematics 2025-11-04 Yaobin Chen , Yu Chen , Jie Han , Jingwen Zhao

Let $H$ be a fixed graph on $v$ vertices. For an $n$-vertex graph $G$ with $n$ divisible by $v$, an $H$-{\em factor} of $G$ is a collection of $n/v$ copies of $H$ whose vertex sets partition $V(G)$. In this paper we consider the threshold…

Combinatorics · Mathematics 2008-03-25 A. Johansson , J. Kahn , V. Vu

We develop a general procedure that finds recursions for statistics counting isomorphic copies of a graph $G_0$ in the common random graph models ${\cal G}(n,m)$ and ${\cal G}(n,p)$. Our results apply when the average degrees of the random…

Combinatorics · Mathematics 2016-08-19 Dudley Stark , Nick Wormald

Random sampling of large Markov matrices with a tunable spectral gap, a nonuniform stationary distribution, and a nondegenerate limiting empirical spectral distribution (ESD) is useful. Fix $c>0$ and $p>0$. Let $A_n$ be the adjacency matrix…

Probability · Mathematics 2015-09-09 Zhiyi Chi