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The absence of intrinsic adjacency relations and orientation systems in hypergraphs creates fundamental challenges for constructing sheaf Laplacians of arbitrary degrees. We resolve these limitations through symmetric simplicial sets…

Machine Learning · Computer Science 2025-08-01 Seongjin Choi , Gahee Kim , Yong-Geun Oh

Graph diffusion models achieve state-of-the-art performance in graph generation but suffer from quadratic complexity in the number of nodes -- and much of their capacity is wasted modeling the absence of edges in sparse graphs. Inspired by…

Machine Learning · Computer Science 2026-05-13 Antoine Siraudin , Christopher Morris

Laplacian operators on finite compact metric graphs are considered under the assumption that matching conditions at graph vertices are of $\delta$ and $\delta'$ types. An infinite series of trace formulae is obtained which link together two…

Spectral Theory · Mathematics 2014-11-06 Yulia Ershova , Irina I. Karpenko , Alexander V. Kiselev

An oriented hypergraph is a hypergraph where each vertex-edge incidence is given a label of $+1$ or $-1$. The adjacency and Laplacian eigenvalues of an oriented hypergraph are studied. Eigenvalue bounds for both the adjacency and Laplacian…

Combinatorics · Mathematics 2015-06-18 Nathan Reff

Quantum graphs have attracted attention from mathematicians for some time. A quantum graph is defined by having a Laplacian on each edge of a metric graph and imposing boundary conditions at the vertices to get an eigenvalue problem. A…

Spectral Theory · Mathematics 2022-07-26 Mats-Erik Pistol , Pavel Kurasov

Because of the significant increase in size and complexity of the networks, the distributed computation of eigenvalues and eigenvectors of graph matrices has become very challenging and yet it remains as important as before. In this paper…

Numerical Analysis · Mathematics 2017-11-27 Konstantin Avrachenkov , Philippe Jacquet , Jithin Sreedharan

We introduce a novel diffusion-based spectral algorithm to tackle regression analysis on high-dimensional data, particularly data embedded within lower-dimensional manifolds. Traditional spectral algorithms often fall short in such…

Machine Learning · Statistics 2024-10-21 Weichun Xia , Jiaxin Jiang , Lei Shi

Recent years have seen extensive research on directed graph sparsification. In this work, we initiate the study of fast fully dynamic spectral and cut sparsification algorithms for directed graphs. We introduce a new notion of spectral…

Data Structures and Algorithms · Computer Science 2025-07-29 Yibin Zhao

Based on matrix perturbation theory, closed-form analytic expansions are studied for a Laplacian eigenvalue of an undirected, possibly weighted graph, which is close to a unique degree in that graph. An approximation is presented to provide…

Spectral Theory · Mathematics 2025-04-29 Piet Van Mieghem , Yingyue Ke

The spectral properties of traditional (dyadic) graphs, where an edge connects exactly two vertices, are widely studied in different applications. These spectral properties are closely connected to the structural properties of dyadic…

Social and Information Networks · Computer Science 2025-06-23 Hao Tian , Shengmin Jin , Reza Zafarani

For discrete weighted graphs there is sufficient literature about the Cheeger cut and the Cheeger problem, but for metric graphs there are few results about these problems. Our aim is to study the Cheeger cut and the Cheeger problem in…

Analysis of PDEs · Mathematics 2022-03-16 José M. Mazón

The first nontrivial lower bound of the worst-case approximation ratio for the maxcut problem was achieved via the dual Cheeger problem, whose optimal value is referred to the dual Cheeger constant $h^+$, and later improved through its…

Spectral Theory · Mathematics 2025-01-22 Sihong Shao , Chuan Yang , Dong Zhang

The ubiquity of massive graph data sets in numerous applications requires fast algorithms for extracting knowledge from these data. We are motivated here by three electrical measures for the analysis of large small-world graphs $G = (V, E)$…

Data Structures and Algorithms · Computer Science 2021-02-09 Eugenio Angriman , Maria Predari , Alexander van der Grinten , Henning Meyerhenke

We study the spectrum of the normalized Laplace operator of a connected graph $\Gamma$. As is well known, the smallest nontrivial eigenvalue measures how difficult it is to decompose $\Gamma$ into two large pieces, whereas the largest…

Combinatorics · Mathematics 2015-03-13 Frank Bauer , Jürgen Jost

Let $G$ be a finite group and $S$ be a symmetric generating set of $G$ with $|S| = d$. We show that if the undirected Cayley sum graph $C_{\Sigma}(G,S)$ is an expander graph and is non-bipartite, then the spectrum of its normalised…

Combinatorics · Mathematics 2019-07-23 Arindam Biswas , Jyoti Prakash Saha

For a connected weighted hypergraph, we give a randomized almost-linear-time solver for the Poisson problem for the cut-based hypergraph Laplacian in the natural input size $P=\sum_{e\in E}|e|$, the sum of hyperedge sizes. For every fixed…

Data Structures and Algorithms · Computer Science 2026-05-01 Yuichi Yoshida

On a compact metric graph, we consider the spectrum of the Laplacian defined with a mix of standard and Dirichlet vertex conditions. A Cheeger-type lower bound on the gap $\lambda_2 - \lambda_1$ is established, with a constant that depends…

Spectral Theory · Mathematics 2023-01-19 David Borthwick , Evans M. Harrell , Haozhe Yu

We study the spectrum of one dimensional integral operators in bounded real intervals of length $2L$, for value of $L$ large. The integral operators are obtained by linearizing a non local evolution equation for a non conserved order…

Mathematical Physics · Physics 2017-01-16 Enza Orlandi , Carlangelo Liverani

The relationships between eigenvalues and eigenvectors of a product graph and those of its factor graphs have been known for the standard products, while characterization of Laplacian eigenvalues and eigenvectors of the Kronecker product of…

Social and Information Networks · Computer Science 2021-02-08 Milan Bašić , Branko Arsić , Zoran Obradović

The Cheeger constant of a graph is the smallest possible ratio between the size of a subgraph and the size of its boundary. It is well known that this constant must be at least $\frac{\lambda_1}{2}$, where $\lambda_1$ is the smallest…

Combinatorics · Mathematics 2019-09-19 Jack Koolen , Greg Markowsky , Zhi Qiao
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