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Related papers: Constructing cospectral hypergraphs

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We compute spectra of symmetric random matrices defined on graphs exhibiting a modular structure. Modules are initially introduced as fully connected sub-units of a graph. By contrast, inter-module connectivity is taken to be incomplete.…

Disordered Systems and Neural Networks · Physics 2009-08-24 G. Ergun , R. Kuehn

Many natural and social systems develop complex networks, that are usually modelled as random graphs. The eigenvalue spectrum of these graphs provides information about their structural properties. While the semi-circle law is known to…

Statistical Mechanics · Physics 2009-11-07 Illes J. Farkas , Imre Derenyi , Albert-Laszlo Barabasi , Tamas Vicsek

Spectral hypergraph theory has recently attracted considerable interest as it provides a natural framework for modeling higher-order relationships beyond classical graphs. In this setting, eigenvalues of adjacency, Laplacian, and…

Combinatorics · Mathematics 2026-04-28 Shashwath S Shetty , K Arathi Bhat

We completely determine the spectrum of an $I$-graph, that is, the eigenvalues of its adjacency matrix. We apply our result to prove known characterizations of connectedness and bipartiteness in $I$-graphs by using an spectral approach.…

Combinatorics · Mathematics 2015-11-12 Allana S. S. de Oliveira , Cybele T. M. Vinagre

A subgraph is constructed by using a subset of vertices and edges of a given graph. There exist many graph properties that are hereditary for subgraphs. Hence, researchers from different communities have paid a great deal of attention in…

Combinatorics · Mathematics 2023-06-06 Kai Siong Yow , Ningyi Liao , Siqiang Luo , Reynold Cheng , Chenhao Ma , Xiaolin Han

We introduce new geometric objects called spectral networks. Spectral networks are networks of trajectories on Riemann surfaces obeying certain local rules. Spectral networks arise naturally in four-dimensional N=2 theories coupled to…

High Energy Physics - Theory · Physics 2015-06-04 Davide Gaiotto , Gregory W. Moore , Andrew Neitzke

Optical spectroscopies provide a powerful tool for harnessing light-matter interactions for unraveling complex electronic features such as the flat bands and nontrivial topologies of materials. These insights are crucial for the development…

Materials Science · Physics 2025-12-11 Ting-Wei Hsu , Zhenyao Fang , Arun Bansil , Qimin Yan

We present progress on the problem of asymptotically describing the adjacency eigenvalues of random and complete uniform hypergraphs. There is a natural conjecture arising from analogy with random matrix theory that connects these spectra…

Combinatorics · Mathematics 2018-01-10 Joshua Cooper

In this paper we consider aspects of geometric observability for hypergraphs, extending our earlier work from the uniform to the nonuniform case. Hypergraphs, a generalization of graphs, allow hyperedges to connect multiple nodes and…

Dynamical Systems · Mathematics 2024-04-12 Joshua Pickard , Cooper Stansbury , Amit Surana , Indika Rajapakse , Anthony Bloch

We investigate when a complete graph $K_n$ with some edges deleted is determined by its adjacency spectrum. It is shown to be the case if the deleted edges form a matching, a complete graph $K_m$ provided $m \leq n-2$, or a complete…

Combinatorics · Mathematics 2012-11-27 Marc Cámara , Willem H. Haemers

Graph-based signal processing techniques have become essential for handling data in non-Euclidean spaces. However, there is a growing awareness that these graph models might need to be expanded into `higher-order' domains to effectively…

Machine Learning · Computer Science 2024-04-15 Mustafa Hajij , Ghada Zamzmi , Theodore Papamarkou , Aldo Guzmán-Sáenz , Tolga Birdal , Michael T. Schaub

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

Construction of graphs with equal eigenvalues (co-spectral graphs) is an interesting problem in spectral graph theory. Seidel switching is a well-known method for generating co-spectral graphs. From a matrix theoretic point of view, Seidel…

Combinatorics · Mathematics 2016-08-30 Supriyo Dutta , Bibhas Adhikari , Subhashish Banerjee

I present a simple graphical method to find the BPS spectra of $A_1$ theories of class S. BPS graphs provide a bridge between spectral networks and BPS quivers, the two main frameworks for the study of BPS states. Here I show how to…

High Energy Physics - Theory · Physics 2017-11-01 Maxime Gabella

Spectrum maps, which provide RF spectrum metrics such as power spectral density for every location in a geographic area, find numerous applications in wireless communications such as interference control, spectrum management, resource…

Signal Processing · Electrical Eng. & Systems 2019-12-02 Yves Teganya , Daniel Romero

We present an efficient algorithm for the construction of a holographic simple tree graph model that realizes a given entropy vector, subject to a specific ``chordality'' condition first introduced in arXiv:2412.18018. We further develop…

High Energy Physics - Theory · Physics 2025-12-23 Veronika E. Hubeny , Massimiliano Rota

Massive networks have shown that the determination of dense subgraphs, where vertices interact a lot, is necessary in order to visualize groups of common interest, and therefore be able to decompose a big graph into smaller structures. Many…

Social and Information Networks · Computer Science 2016-04-29 Etienne Callies , Tomás Yany-Anich

Let $n$ be any positive integer and let $F_n$ be the friendship (or Dutch windmill) graph with $2n+1$ vertices and $3n$ edges. Here we study graphs with the same adjacency spectrum as the $F_n$. Two graphs are called cospectral if the…

Combinatorics · Mathematics 2013-07-23 Alireza Abdollahi , Shahrooz Janbaz , Mohammad Reza Oboudi

Graph spectra are an important class of structural features on graphs that have shown promising results in enhancing Graph Neural Networks (GNNs). Despite their widespread practical use, the theoretical understanding of the power of…

Machine Learning · Computer Science 2025-03-04 Jingchu Gai , Yiheng Du , Bohang Zhang , Haggai Maron , Liwei Wang

A threshold graph G on n vertices is defined by binary sequence of length n. In this paper we present an explicit formula for computing the characteristic polynomial of a threshold graph from its binary sequence. Applications include…

Combinatorics · Mathematics 2018-06-20 J. Lazzarin , O. F. Márquez , F. Tura
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