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We show that for every $n$-vertex graph with at least one edge, its treewidth is greater than or equal to $n \lambda_{2} / (\Delta + \lambda_{2}) - 1$, where $\Delta$ and $\lambda_{2}$ are the maximum degree and the second smallest…

Combinatorics · Mathematics 2024-04-15 Tatsuya Gima , Tesshu Hanaka , Kohei Noro , Hirotaka Ono , Yota Otachi

We characterize the spectrum of the Laplacian of graphs composed of one or two finite or infinite chains connected to a complete graph. We show the existence of localized eigenvectors of two types, eigenvectors that vanish exactly outside…

Spectral Theory · Mathematics 2020-02-21 J. -G. Caputo , G. Cruz-Pacheco , A. Knippel , P. Panayotaros

This paper establishes new upper bounds for the sum of the $k$ largest eigenvalues of symmetric matrices. When applied to the adjacency matrix of a graph, our results improve upon a related bound due to Mohar {\bf [On the sum of k largest…

Combinatorics · Mathematics 2026-05-27 Shaowei Sun , Yaping Min , Kinkar Chandra Das

To minimize or upper-bound the value of a function "robustly", we might instead minimize or upper-bound the "epsilon-robust regularization", defined as the map from a point to the maximum value of the function within an epsilon-radius. This…

Optimization and Control · Mathematics 2010-06-10 Adrian S. Lewis , C. H. Jeffrey Pang

In this article we prove the equivalence of certain inequalities for Riesz means of eigenvalues of the Dirichlet Laplacian with a classical inequality of Kac. Connections are made via integral transforms including those of Laplace,…

Spectral Theory · Mathematics 2007-12-27 Evans M. Harrell , Lotfi Hermi

We give a generalized curvature-dimension inequality connecting the geometry of sub-Riemannian manifolds with the properties of its sub-Laplacian. This inequality is valid on a large class of sub-Riemannian manifolds obtained from…

Differential Geometry · Mathematics 2015-07-30 Erlend Grong , Anton Thalmaier

Recently, much of the existing work in manifold learning has been done under the assumption that the data is sampled from a manifold without boundaries and singularities or that the functions of interest are evaluated away from such points.…

Artificial Intelligence · Computer Science 2012-11-29 Mikhail Belkin , Qichao Que , Yusu Wang , Xueyuan Zhou

In this paper, we study the Laplacian matching polynomial of a graph and the effect of adding edges to a graph on the roots (called Laplacian matching roots) of this polynomial. In particular, we investigate the conditions under which the…

Combinatorics · Mathematics 2025-09-04 Yi Wang , Hai-Jian Cui , Sebastian M. Cioabă

We consider the action of the (combinatorial) Laplacian of a finite and simple graph on integer vectors. By a \emph{Laplacian monopole} we mean an image vector negative at exactly one coordinate associated with a vertex. We consider a…

Combinatorics · Mathematics 2020-06-11 Cong X. Kang , Gretchen L. Matthews , Justin D. Peachey

We develop eigenvalue estimates for the Laplacians on discrete and metric graphs using different types of boundary conditions at the vertices of the metric graph. Via an explicit correspondence of the equilateral metric and discrete graph…

Spectral Theory · Mathematics 2008-04-08 Olaf Post , Fernando Lledo

The eigenvectors for graph $1$-Laplacian possess some sort of localization property: On one hand, any nodal domain of an eigenvector is again an eigenvector with the same eigenvalue; on the other hand, one can pack up an eigenvector for a…

Spectral Theory · Mathematics 2017-01-04 K. C. Chang , Sihong Shao , Dong Zhang

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

We study the location of the spectrum of the Laplacian on compact metric graphs with complex Robin-type vertex conditions, also known as $\delta$ conditions, on some or all of the graph vertices. We classify the eigenvalue asymptotics as…

Spectral Theory · Mathematics 2020-10-06 James B. Kennedy , Robin Lang

Let $G$ be a graph with $p(G)$ pendant vertices and $q(G)$ quasi-pendant vertices. Denote by $m_{L(G)}(\lambda)$ the multiplicity of $\lambda$ as a Laplacian eigenvalue of $G$. Let $\overline{G}$ be the reduced graph of $G$, which can be…

Combinatorics · Mathematics 2025-07-09 Fenglei Tian , Dein Wong

In this paper, we investigate the eigenvalues of the Laplacian matrix of the "graph of graphs", in which cubic graphs of order n are joined together using Whitehead moves. Our work follows recent results from arXiv:2303.13923 , which…

Combinatorics · Mathematics 2024-05-24 Michael Li

Determining and analyzing the spectra of graphs is an important and exciting research topic in theoretical computer science. The eigenvalues of the normalized Laplacian of a graph provide information on its structural properties and also on…

Combinatorics · Mathematics 2016-05-20 Pinchen Xie , Zhongzhi Zhang , Francesc Comellas

The main objective of the present work is to study the negative spectrum of (differential) Laplace operators on metric graphs as well as their resolvents and associated heat semigroups. We prove an upper bound on the number of negative…

Mathematical Physics · Physics 2007-05-23 Vadim Kostrykin , Robert Schrader

Vertex similarity is a major problem in network science with a wide range of applications. In this work we provide novel perspectives on finding (dis)similar vertices within a network and across two networks with the same number of vertices…

Social and Information Networks · Computer Science 2013-05-28 Charalampos E. Tsourakakis

We discuss Laplacian spectrum on a finite metric graph with vertex couplings violating the time-reversal invariance. For the class of star graphs we determine, under the condition of a fixed total edge length, the configurations for which…

Mathematical Physics · Physics 2025-03-14 Pavel Exner , Jonathan Rohleder

We present a novel spectral embedding of graphs that incorporates weights assigned to the nodes, quantifying their relative importance. This spectral embedding is based on the first eigenvectors of some properly normalized version of the…

Machine Learning · Computer Science 2018-10-04 Thomas Bonald , Alexandre Hollocou , Marc Lelarge
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