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In the random geometric graph model $\mathsf{Geo}_d(n,p)$, we identify each of our $n$ vertices with an independently and uniformly sampled vector from the $d$-dimensional unit sphere, and we connect pairs of vertices whose vectors are…

Probability · Mathematics 2021-11-23 Siqi Liu , Sidhanth Mohanty , Tselil Schramm , Elizabeth Yang

We give faster algorithms for producing sparse approximations of the transition matrices of $k$-step random walks on undirected, weighted graphs. These transition matrices also form graphs, and arise as intermediate objects in a variety of…

Data Structures and Algorithms · Computer Science 2017-02-21 Gorav Jindal , Pavel Kolev , Richard Peng , Saurabh Sawlani

We revisit the probabilistic construction of sparse random matrices where each column has a fixed number of nonzeros whose row indices are drawn uniformly at random with replacement. These matrices have a one-to-one correspondence with the…

Information Theory · Computer Science 2013-07-16 Bubacarr Bah , Jared Tanner

We prove the following theorem. Given a planar graph $G$ and an integer $k$, it is possible in polynomial time to randomly sample a subset $A$ of vertices of $G$ with the following properties: (i) $A$ induces a subgraph of $G$ of treewidth…

Data Structures and Algorithms · Computer Science 2016-04-21 Fedor V. Fomin , Daniel Lokshtanov , Dániel Marx , Marcin Pilipczuk , Michał Pilipczuk , Saket Saurabh

We investigate the statistics of the largest eigenvalue, $\lambda_{\rm max}$, in an ensemble of $N\times N$ large ($N\gg 1$) sparse adjacency matrices, $A_N$. The most attention is paid to the distribution and typical fluctuations of…

Statistical Mechanics · Physics 2023-06-14 Bogdan Slavov , Kirill Polovnikov , Sergei Nechaev , Nikita Pospelov

In this paper we show that all nodes can be found optimally for almost all random Erd\H{o}s-R\'enyi ${\mathcal G}(n,p)$ graphs using continuous-time quantum spatial search procedure. This works for both adjacency and Laplacian matrices,…

Quantum Physics · Physics 2018-03-05 Adam Glos , Aleksandra Krawiec , Ryszard Kukulski , Zbigniew Puchała

We compute analytically, for large N, the probability distribution of the number of positive eigenvalues (the index N_{+}) of a random NxN matrix belonging to Gaussian orthogonal (\beta=1), unitary (\beta=2) or symplectic (\beta=4)…

Statistical Mechanics · Physics 2015-05-14 Satya N. Majumdar , Celine Nadal , Antonello Scardicchio , Pierpaolo Vivo

A theorem of Hoffman gives an upper bound on the independence ratio of regular graphs in terms of the minimum $\lambda_{\min}$ of the spectrum of the adjacency matrix. To complement this result we use random eigenvectors to gain lower…

Probability · Mathematics 2016-08-11 Viktor Harangi , Bálint Virág

Invariant ensemble, which are characterised by the joint distribution of eigenvalues $P(\lambda_1,\ldots,\lambda_N)$, play a central role in random matrix theory. We consider the truncated linear statistics $L_K = \sum_{n=1}^K f(\lambda_n)$…

Statistical Mechanics · Physics 2022-03-09 Aurélien Grabsch

We study the k-wise independent relaxation of the usual model G(N,p) of random graphs where, as in this model, N labeled vertices are fixed and each edge is drawn with probability p, however, it is only required that the distribution of any…

Combinatorics · Mathematics 2008-04-09 Noga Alon , Asaf Nussboim

We prove a local law for the adjacency matrix of the Erd\H{o}s-R\'enyi graph $G(N, p)$ in the supercritical regime $ pN \geq C\log N$ where $G(N,p)$ has with high probability no isolated vertices. In the same regime, we also prove the…

Probability · Mathematics 2019-01-16 Yukun He , Antti Knowles , Matteo Marcozzi

We study random k-lifts of large, but otherwise arbitrary graphs G. We prove that, with high probability, all eigenvalues of the adjacency matrix of the lift that are not eigenvalues of G are of the order (D ln (kn))^{1/2}, where D is the…

Combinatorics · Mathematics 2011-09-07 Roberto Imbuzeiro Oliveira

We introduce a powerful analytic method to study the statistics of the number $\mathcal{N}_{\textbf{A}}(\gamma)$ of eigenvalues inside any contour $\gamma \in \mathbb{C}$ for infinitely large non-Hermitian random matrices ${\textbf A}$. Our…

Disordered Systems and Neural Networks · Physics 2021-06-09 Antonio Tonatiúh Ramos Sánchez , Edgar Guzmán-González , Isaac Pérez Castillo , Fernando L. Metz

For any $\alpha\in (0,1)$ and any $n^{\alpha}\leq d\leq n/2$, we show that $\lambda(G)\leq C_\alpha \sqrt{d}$ with probability at least $1-\frac{1}{n}$, where $G$ is the uniform random $d$-regular graph on $n$ vertices, $\lambda(G)$ denotes…

Probability · Mathematics 2019-01-07 Konstantin Tikhomirov , Pierre Youssef

For any fixed simple graph $H=(V,E)$ and any fixed $u>0$, we establish the leading order of the exponential rate function for the probability that the number of copies of $H$ in the Erd\H{o}s--R\'enyi graph $G(n,p)$ exceeds its expectation…

Probability · Mathematics 2020-04-28 Nicholas A. Cook , Amir Dembo

We revisit the asymptotic analysis of probabilistic construction of adjacency matrices of expander graphs proposed in [4]. With better bounds we derived a new reduced sample complexity for the number of nonzeros per column of these…

Information Theory · Computer Science 2018-05-17 Bubacarr Bah , Jared Tanner

We revisit the probabilistic construction of sparse random matrices where each column has a fixed number of nonzeros whose row indices are drawn uniformly at random. These matrices have a one-to-one correspondence with the adjacency…

Information Theory · Computer Science 2013-07-25 Bubacarr Bah , Jared Tanner

Let $\mathcal{P}_{\beta}^{(V)} (N_{\cal I})$ be the probability that a $N\times N$ $\beta$-ensemble of random matrices with confining potential $V(x)$ has $N_{\cal I}$ eigenvalues inside an interval ${\cal I}=[a,b]$ of the real line. We…

Statistical Mechanics · Physics 2016-09-15 Ricardo Marino , Satya N. Majumdar , Gregory Schehr , Pierpaolo Vivo

We propose the following model of a random graph on n vertices. Let F be a distribution in R_+^{n(n-1)/2} with a coordinate for every pair i$ with 1 \le i,j \le n. Then G_{F,p} is the distribution on graphs with n vertices obtained by…

Combinatorics · Mathematics 2011-08-09 Alan Frieze , Santosh Vempala , Juan Vera

In this paper we consider the task of estimating the non-zero pattern of the sparse inverse covariance matrix of a zero-mean Gaussian random vector from a set of iid samples. Note that this is also equivalent to recovering the underlying…

Machine Learning · Computer Science 2012-02-28 Christopher C. Johnson , Ali Jalali , Pradeep Ravikumar