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We prove improved bounds on how localized an eigenvector of a high girth regular graph can be, and present examples showing that these bounds are close to sharp. This study was initiated by Brooks and Lindenstrauss (2009) who relied on the…

Combinatorics · Mathematics 2021-08-06 Shirshendu Ganguly , Nikhil Srivastava

We study a model of random graphs where each edge is drawn independently (but not necessarily identically distributed) from the others, and then assigned a random weight. When the mean degree of such a graph is low, it is known that the…

Probability · Mathematics 2022-02-09 Ludovic Stephan , Laurent Massoulié

We describe the non-backtracking spectrum of a stochastic block model with connection probabilities $p_{\mathrm{in}}, p_{\mathrm{out}} = \omega(\log n)/n$. In this regime we answer a question posed in Dall'Amico and al. (2019) regarding the…

Probability · Mathematics 2021-09-13 Simon Coste , Yizhe Zhu

Motivated by community detection, we characterise the spectrum of the non-backtracking matrix $B$ in the Degree-Corrected Stochastic Block Model. Specifically, we consider a random graph on $n$ vertices partitioned into two equal-sized…

Probability · Mathematics 2017-05-19 Lennart Gulikers , Marc Lelarge , Laurent Massoulié

A non-backtracking walk on a graph is a directed path such that no edge is the inverse of its preceding edge. The non-backtracking matrix of a graph is indexed by its directed edges and can be used to count non-backtracking walks of a given…

Probability · Mathematics 2015-04-23 Charles Bordenave , Marc Lelarge , Laurent Massoulié

In the case of graph partitioning, the emergence of localized eigenvectors can cause the standard spectral method to fail. To overcome this problem, the spectral method using a non-backtracking matrix was proposed. Based on numerical…

Social and Information Networks · Computer Science 2016-03-18 Tatsuro Kawamoto

Much effort has been spent on characterizing the spectrum of the non-backtracking matrix of certain classes of graphs, with special emphasis on the leading eigenvalue or the second eigenvector. Much less attention has been paid to the…

Combinatorics · Mathematics 2020-07-29 Leo Torres

We consider the ensemble of adjacency matrices of Erd\H{o}s-R\'{e}nyi random graphs, that is, graphs on $N$ vertices where every edge is chosen independently and with probability $p\equiv p(N)$. We rescale the matrix so that its bulk…

Probability · Mathematics 2013-07-12 László Erdős , Antti Knowles , Horng-Tzer Yau , Jun Yin

The spectrum of the non-backtracking matrix plays a crucial role in determining various structural and dynamical properties of networked systems, ranging from the threshold in bond percolation and non-recurrent epidemic processes, to…

Physics and Society · Physics 2021-01-11 Romualdo Pastor-Satorras , Claudio Castellano

We consider the uniform random $d$-regular graph on $N$ vertices, with $d \in [N^\alpha, N^{2/3-\alpha}]$ for arbitrary $\alpha > 0$. We prove that in the bulk of the spectrum the local eigenvalue correlation functions and the distribution…

Probability · Mathematics 2019-08-21 Roland Bauerschmidt , Jiaoyang Huang , Antti Knowles , Horng-Tzer Yau

The non-backtracking operator was recently shown to give a redemption for spectral clustering in sparse graphs. In this paper we consider non-backtracking operator for Ising model on a general graph with a general coupling distribution by…

Disordered Systems and Neural Networks · Physics 2014-09-12 Pan Zhang

Analyzing the spectral behavior of random matrices with dependency among entries is a challenging problem. The adjacency matrix of the random $d$-regular graph is a prominent example that has attracted immense interest. A crucial spectral…

Probability · Mathematics 2023-06-07 Jaehun Lee , Kyeongsik Nam

We investigate the spectrum of the non-backtracking matrix of a graph. In particular, we show how to obtain eigenvectors of the non-backtracking matrix in terms of eigenvectors of a smaller matrix. Furthermore, we find an expression for the…

Combinatorics · Mathematics 2020-11-19 Cory Glover , Mark Kempton

In case of sparse graphs, relation between the real eigenvalues of the non-backtracking matrix and those of the non-backtracking transition probability matrix is considered with respect to vertex clustering. For this purpose, the random…

Combinatorics · Mathematics 2026-05-26 Marianna Bolla

We consider the bulk eigenvalue statistics of Laplacian matrices of large Erd\H{o}s-R\'enyi random graphs in the regime $p \geq N^{\delta}/N$ for any fixed $\delta >0$. We prove a local law down to the optimal scale $\eta \gtrsim N^{-1}$…

Probability · Mathematics 2015-10-22 Jiaoyang Huang , Benjamin Landon

The spectrum of the nonbacktracking matrix associated to a network is known to contain fundamental information regarding percolation properties of the network. Indeed, the inverse of its leading eigenvalue is often used as an estimate for…

Physics and Society · Physics 2025-01-30 James Martin , Tim Rogers , Luca Zanetti

We consider the community detection problem in a sparse $q$-uniform hypergraph $G$, assuming that $G$ is generated according to the Hypergraph Stochastic Block Model (HSBM). We prove that a spectral method based on the non-backtracking…

Probability · Mathematics 2024-01-29 Ludovic Stephan , Yizhe Zhu

For random $d$-regular graphs on $N$ vertices with $1 \ll d \ll N^{2/3}$, we develop a $d^{-1/2}$ expansion of the local eigenvalue distribution about the Kesten-McKay law up to order $d^{-3}$. This result is valid up to the edge of the…

Probability · Mathematics 2021-07-06 Roland Bauerschmidt , Jiaoyang Huang , Antti Knowles , Horng-Tzer Yau

We prove delocalization of eigenvectors of vertex-transitive graphs via elementary estimates of the spectral projector. We recover in this way known results which were formerly proved using representation theory. Similar techniques show…

Spectral Theory · Mathematics 2025-10-15 Nicolas Burq , Cyril Letrouit

We analyse the eigenvectors of the adjacency matrix of the Erd\H{o}s-R\'enyi graph on $N$ vertices with edge probability $\frac{d}{N}$. We determine the full region of delocalization by determining the critical values of $\frac{d}{\log N}$…

Probability · Mathematics 2021-12-03 Johannes Alt , Raphael Ducatez , Antti Knowles
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