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We give a delocalization estimate for eigenfunctions of the discrete Laplacian on large $d+1$-regular graphs, showing that any subset of the graph supporting $\epsilon$ of the $L^2$ mass of an eigenfunction must be large. For graphs…

Dynamical Systems · Mathematics 2009-12-17 Shimon Brooks , Elon Lindenstrauss

Consider any random graph model where potential edges appear independently, with possibly different probabilities, and assume that the minimum expected degree is omega(ln n). We prove that the adjacency matrix and the Laplacian of that…

Combinatorics · Mathematics 2010-02-10 Roberto Imbuzeiro Oliveira

The second-largest eigenvalue and second-smallest Laplacian eigenvalue of a graph are measures of its connectivity. These eigenvalues can be used to analyze the robustness, resilience, and synchronizability of networks, and are related to…

Combinatorics · Mathematics 2018-07-20 Aida Abiad , Boris Brimkov , Xavier Martinez-Rivera , O Suil , Jingmei Zhang

In this article we consider resistance matrix of a connected graph. For unweighted graph we study some necessary and sufficient conditions for resistance regular graphs. Also we find some relationship between Laplacian matrix and resistance…

Combinatorics · Mathematics 2018-03-28 Deepak Sarma

Resistance distance has been studied extensively in the past years, with the majority of previous studies devoted to undirected networks, in spite of the fact that various realistic networks are directed. Although several generalizations of…

Networking and Internet Architecture · Computer Science 2023-02-09 Mingzhe Zhu , Liwang Zhu , Huan Li , Wei Li , Zhongzhi Zhang

In this paper we prove the first quantitative convergence rates for the graph infinity Laplace equation for length scales at the connectivity threshold. In the graph-based semi-supervised learning community this equation is also known as…

Probability · Mathematics 2024-02-23 Leon Bungert , Jeff Calder , Tim Roith

Existing approaches to analyzing the asymptotics of graph Laplacians typically assume a well-behaved kernel function with smoothness assumptions. We remove the smoothness assumption and generalize the analysis of graph Laplacians to include…

Machine Learning · Statistics 2011-01-31 Daniel Ting , Ling Huang , Michael Jordan

The paper is a brief survey of some recent new results and progress of the Laplacian spectra of graphs and complex networks (in particular, random graph and the small world network). The main contents contain the spectral radius of the…

Combinatorics · Mathematics 2011-11-15 Ya-Hong Chen , Rong-Ying Pan , Xiao-Dong Zhang

Large-scale graph machine learning is challenging as the complexity of learning models scales with the graph size. Subsampling the graph is a viable alternative, but sampling on graphs is nontrivial as graphs are non-Euclidean. Existing…

Machine Learning · Computer Science 2024-10-10 Thien Le , Luana Ruiz , Stefanie Jegelka

In this paper, we consider the weighted graph matching problem with partially disclosed correspondences between a number of anchor nodes. Our construction exploits recently introduced node signatures based on graph Laplacians, namely the…

Computer Vision and Pattern Recognition · Computer Science 2018-04-12 Nan Hu , Raif M. Rustamov , Leonidas Guibas

The fault tolerance of random graphs with unbounded degrees with respect to connectivity is investigated, which relates to the reliability of wireless sensor networks with unreliable relay nodes. The model evaluates the network breakdown…

Disordered Systems and Neural Networks · Physics 2019-06-05 Satoshi Takabe , Takafumi Nakano , Tadashi Wadayama

We prove an upper bound for the independence number of a graph in terms of the largest Laplacian eigenvalue, and of a certain induced subgraph. Our bound is a refinement of a well-known Hoffman-type bound.

Combinatorics · Mathematics 2023-11-17 Bogdan Nica

A metrized graph is a compact singular 1-manifold endowed with a metric. A given metrized graph can be modelled by a family of weighted combinatorial graphs. If one chooses a sequence of models from this family such that the vertices become…

Classical Analysis and ODEs · Mathematics 2007-05-23 X. W. C. Faber

In a paper by Nishikawa and Motter, a quantity called the normalized spread of the Laplacian eigenvalues is used to measure the synchronizability of certain network dynamics. Through simulations, and without theoretical validation, it is…

Optimization and Control · Mathematics 2026-01-09 Susie Lu , John Urschel , Ji Liu

We present monotonicity inequalities for certain functions involving eigenvalues of $p$-Laplacians on signed graphs with respect to $p$. Inspired by such monotonicity, we propose new spectrum-based graph invariants, called (variational)…

Spectral Theory · Mathematics 2023-11-01 Chuanyuan Ge , Shiping Liu , Dong Zhang

Given an undirected graph, the resistance distance between two nodes is the resistance one would measure between these two nodes in an electrical network if edges were resistors. Summing these distances over all pairs of nodes yields the…

Information Theory · Computer Science 2015-10-01 Nicolas Boumal , Xiuyuan Cheng

We offer a new method for proving that the maximal eigenvalue of the normalized graph Laplacian of a graph with $n$ vertices is at least $\frac{n+1}{n-1}$ provided the graph is not complete and that equality is attained if and only if the…

Spectral Theory · Mathematics 2021-04-07 Jürgen Jost , Raffaella Mulas , Florentin Münch

Greb\'ik and Rocha [Fractional Isomorphism of Graphons, Combinatorica 42, pp 365-404 (2022)] extended the well studied notion of fractional isomorphism of graphs to graphons. We prove that fractionally isomorphic graphons can be…

Combinatorics · Mathematics 2023-09-22 Jan Hladký , Eng Keat Hng

We obtain a general formula for the resistance distance (or effective resistance) between any pair of nodes in a general family of graphs which we call flower graphs. Flower graphs are obtained from identifying nodes of multiple copies of a…

Combinatorics · Mathematics 2020-07-08 Nolan Faught , Mark Kempton , Adam Knudson

This paper studies how close random graphs are typically to their expectations. We interpret this question through the concentration of the adjacency and Laplacian matrices in the spectral norm. We study inhomogeneous Erd\"os-R\'enyi random…

Probability · Mathematics 2016-08-10 Can M. Le , Elizaveta Levina , Roman Vershynin
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