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In this paper, we give tight bounds for the normalized Laplacian eigenvalues of hypergraphs that are not necessarily uniform, and provide an edge version interlacing theorem, a Cheeger inequality, and a discrepancy inequality that are…

Combinatorics · Mathematics 2025-04-15 Leyou Xu , Bo Zhou

The celebrated Cheeger's Inequality establishes a bound on the edge expansion of a graph via its spectrum. This inequality is central to a rich spectral theory of graphs, based on studying the eigenvalues and eigenvectors of the adjacency…

Discrete Mathematics · Computer Science 2016-05-06 T-H. Hubert Chan , Anand Louis , Zhihao Gavin Tang , Chenzi Zhang

We study the convergence of the graph Laplacian of a random geometric graph generated by an i.i.d. sample from a $m$-dimensional submanifold $M$ in $R^d$ as the sample size $n$ increases and the neighborhood size $h$ tends to zero. We show…

Machine Learning · Statistics 2018-01-31 Nicolas Garcia Trillos , Moritz Gerlach , Matthias Hein , Dejan Slepcev

For a given infinite connected graph $G=(V,E)$ and an arbitrary but fixed conductance function $c$, we study an associated graph Laplacian $\Delta_{c}$; it is a generalized difference operator where the differences are measured across the…

Functional Analysis · Mathematics 2015-06-19 Palle Jorgensen , Feng Tian

This note introduces a result on the location of eigenvalues, i.e., the spectrum, of the Laplacian for a family of undirected graphs with self-loops. We extend on the known results for the spectrum of undirected graphs without self-loops or…

Optimization and Control · Mathematics 2015-06-09 Behcet Acikmese

We extend the results given by Colbois, Dryden and El Soufi on the relationships between the eigenvalues of the Laplacian and an extrinsic invariant called intersection index, in two directions. First, we replace this intersection index by…

Spectral Theory · Mathematics 2013-04-30 Asma Hassannezhad

Let $G$ be a finite solvable group, let $Irr(G)$ be the set of all complex irreducible characters of $G$ and let $cd(G)$ be the set of all degrees of characters in $Irr(G).$ Let $\rho(G)$ be the set of primes that divide degrees in $cd(G).$…

Group Theory · Mathematics 2023-08-08 G. Sivanesan , C. Selvaraj

Here we study the spectral properties of an underlying weighted graph of a non-uniform hypergraph by introducing different connectivity matrices, such as adjacency, Laplacian and normalized Laplacian matrices. We show that different…

Combinatorics · Mathematics 2019-03-28 Anirban Banerjee

For a regular polyhedron (or polygon) centered at the origin, the coordinates of the vertices are eigenvectors of the graph Laplacian for the skeleton of that polyhedron (or polygon) associated with the first (non-trivial) eigenvalue. In…

Optimization and Control · Mathematics 2022-06-22 Braxton Osting

In this paper, we characterize all graphs with eigenvectors of the signless Laplacian and adjacency matrices with components equal to $\{- 1, 0, 1\}.$ We extend the graph parameter max $k$-cut to square matrices and prove a general sharp…

Combinatorics · Mathematics 2022-11-29 Jorge Alencar , Leonardo de Lima , Vladimir Nikiforov

A basic fact in spectral graph theory is that the number of connected components in an undirected graph is equal to the multiplicity of the eigenvalue zero in the Laplacian matrix of the graph. In particular, the graph is disconnected if…

Metric Geometry · Mathematics 2014-11-24 James R. Lee , Shayan Oveis Gharan , Luca Trevisan

Let $G$ be a connected simple graph of order $n$. Let $\rho_1(G)\geq \rho_2(G)\geq \cdots \geq \rho_{n-1}(G)> \rho_n(G)=0$ be the eigenvalues of the normalized Laplacian matrix $\mathcal{L}(G)$ of $G$. Denote by $m(\rho_i)$ the multiplicity…

Combinatorics · Mathematics 2020-12-23 Fenglei Tian , Yiju Wang

The largest eigenvalue of a matrix is always larger or equal than its largest diagonal entry. We show that for a large class of random Laplacian matrices, this bound is essentially tight: the largest eigenvalue is, up to lower order terms,…

Probability · Mathematics 2015-07-28 Afonso S. Bandeira

In this paper, we establish the relation between classic invariants of graphs and their integer Laplacian eigenvalues, focusing on a subclass of chordal graphs, the strictly chordal graphs, and pointing out how their computation can be…

Discrete Mathematics · Computer Science 2020-08-05 Nair Abreu , Claudia Marcela Justel , Lilian Markenzon

In this article we introduce a definition of k-uniform thresholds hypergraphs through a binary sequence, a natural extension of the classical definition for thresholds graphs. We characterize some of its eigenvalues and multiplicities by…

Combinatorics · Mathematics 2026-02-26 Miriam Abdón , Lucas Portugal , Renata Del-Vecchio , Renata de Freitas

We compute the eigenvalues with multiplicities of the Lichnerowicz Laplacian acting on the space of symmetric covariant tensor fields on the Euclidian sphere $S^n$. The spaces of symmetric eigentensors are explicitly given.

Differential Geometry · Mathematics 2007-05-23 M. Boucetta

We give a construction of a class of magnetic Laplacian operators on finite directed graphs. We study some general combinatorial and algebraic properties of operators in this class before applying the Harrell-Stubbe Averaged Variational…

Spectral Theory · Mathematics 2018-06-05 John Dever

Graph disaggregation is a technique used to address the high cost of computation for power law graphs on parallel processors. The few high-degree vertices are broken into multiple small-degree vertices, in order to allow for more efficient…

Numerical Analysis · Mathematics 2016-05-04 Xiaozhe Hu , John C. Urschel , Ludmil T. Zikatanov

We study an eigenvalue problem for the Laplacian on a compact K\"{a}hler manifold. Considering the $k$-th eigenvalue $\lambda_{k}$ as a functional on the space of K\"{a}hler metrics with fixed volume on a compact complex manifold, we…

Differential Geometry · Mathematics 2024-11-27 Kazumasa Narita

Spectral methods that are based on eigenvectors and eigenvalues of discrete graph Laplacians, such as Diffusion Maps and Laplacian Eigenmaps are often used for manifold learning and non-linear dimensionality reduction. It was previously…

Numerical Analysis · Mathematics 2015-06-02 Amit Singer , Hau-tieng Wu
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