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The notions of spectral measures and spectral classes, which are well known for graphs, are generalized and investigated for oriented hypergraphs.

Combinatorics · Mathematics 2021-02-16 Raffaella Mulas

We present the first steps towards the determination of the signed graphs for which the adjacency matrix has all but at most two eigenvalues equal to 1 or -1. Here we deal with the disconnected, the bipartite and the complete signed graphs.…

Combinatorics · Mathematics 2021-09-07 Willem H. Haemers , Hatice Topcu

The index of a signed graph is the largest eigenvalue of its adjacency matrix. For positive integers $n$ and $m\le n^2/4$, we determine the maximal index of complete signed graphs with $n$ vertices and $m$ negative edges. This settles (the…

Combinatorics · Mathematics 2021-05-04 Ebrahim Ghorbani , Arezoo Majidi

Signed graphs, which are characterized by both positive and negative edge weights, have recently attracted significant attention in the field of graph signal processing (GSP). Existing works on signed graph learning typically assume that…

Signal Processing · Electrical Eng. & Systems 2025-09-12 Rong Ye , Xue-Qin Jiang , Hui Feng , Jian Wang , Runhe Qiu

A graph is a mathematical object consisting of a set of vertices and a set of edges connecting vertices. Graphs can be drawn on paper in various ways, but until recently all published methods of drawing graphs have had undesirable…

Human-Computer Interaction · Computer Science 2014-05-22 Bob Blakley , G R Blakley , Sean M Blakley

We construct infinitely many signed graphs having symmetric spectrum, by using the NEPS and rooted product of signed graphs. We also present a method for constructing large cospectral signed graphs. Although the obtained family contains…

Combinatorics · Mathematics 2019-09-17 Farzaneh Ramezani

The definition of edge-regularity in graphs is a relaxation of the definition of strong regularity, so strongly regular graphs are edge-regular and, not surprisingly, the family of edge-regular graphs is much larger and more diverse than…

Combinatorics · Mathematics 2025-04-14 Jared DeLeo

Spectral analysis connects graph structure to the eigenvalues and eigenvectors of associated matrices. Much of spectral graph theory descends directly from spectral geometry, the study of differentiable manifolds through the spectra of…

Social and Information Networks · Computer Science 2019-05-24 Kun Dong , Austin R. Benson , David Bindel

The paper deals with some spectral properties of (mostly infinite) quantum and combinatorial graphs. Quantum graphs have been intensively studied lately due to their numerous applications to mesoscopic physics, nanotechnology, optics, and…

Mathematical Physics · Physics 2009-11-10 Peter Kuchment

A signed graph is a graph in which each edge has a positive or negative sign. In this article, first we characterize the distance compatibility in the case of a connected signed graph and discussed the distance compatibility criterion for…

Combinatorics · Mathematics 2020-09-21 T. V. Shijin , P. Soorya , K. Shahul Hameed , K. A. Germina

Recently the collection $\cal G$ of all signed graphs for which the adjacency matrix has all but at most two eigenvalues equal to $\pm 1$ has been determined. Here we investigate $\cal G$ for cospectral pairs, and for signed graphs…

Combinatorics · Mathematics 2023-11-30 Willem H. Haemers , Hatice Topcu

A signed graph product is defined for a new product, and initially the unsigned graph product's Laplacian spectrum and signless Laplacian spectrum are found. Next, for the signed graph product, the adjacency spectrum, Laplacian spectrum,…

Combinatorics · Mathematics 2024-05-16 Bishal Sonar , Ravi Srivastava

We consider signed networks in which connections or edges can be either positive (friendship, trust, alliance) or negative (dislike, distrust, conflict). Early literature in graph theory theorized that such networks should display…

Social and Information Networks · Computer Science 2019-01-30 Alec Kirkley , George T. Cantwell , M. E. J. Newman

A signed graph has edge signs. A gain graph has oriented edge gains drawn from a group. We define the combination of the two for the abelian case, in which each oriented edge of a signed graph has a gain from an abelian group, concentrating…

Combinatorics · Mathematics 2022-06-22 Laura Anderson , Ting Su , Thomas Zaslavsky

Determining whether two graphs are structurally identical is a fundamental problem with applications spanning mathematics, computer science, chemistry, and network science. Despite decades of study, graph isomorphism remains a challenging…

Computational Physics · Physics 2026-04-10 Sara Najem , Amer E. Mouawad

Signed graphs have appeared in a broad variety of applications, ranging from social networks to biological networks, from distributed control and computation to power systems. In this paper, we investigate spectral properties of signed…

Systems and Control · Electrical Eng. & Systems 2020-09-09 Wei Chen , Dan Wang , Ji Liu , Yongxin Chen , Sei Zhen Khong , Tamer Başar , Karl H. Johansson , Li Qiu

Signed graphs have their edges labeled either as positive or negative. $\rho(M)$ denote the $M$-spectral radius of $\Sigma$, where $M=M(\Sigma)$ is a real symmetric graph matrix of $\Sigma$. Obviously,…

Combinatorics · Mathematics 2022-01-19 Dan Li , Huiqiu Lin , Jixiang Meng

We introduce the concept of deficiency in signed graphs. The deficiency of a coloration is the number of unused colors. We classify the deficiency of 2-chromatic graphs. There are four decision problems about the minimum and maximum…

Combinatorics · Mathematics 2020-06-01 Amelia R. W. Mattern

Large graphs can be found in a wide array of scientific fields ranging from sociology and biology to scientometrics and computer science. Their analysis is by no means a trivial task due to their sheer size and complex structure. Such…

Social and Information Networks · Computer Science 2017-02-24 Georgios Drakopoulos , Stavros Kontopoulos , Christos Makris , Vasileios Megalooikonomou

Real-world data is often represented through the relationships between data samples, forming a graph structure. In many applications, it is necessary to learn this graph structure from the observed data. Current graph learning research has…

Machine Learning · Statistics 2025-07-15 Abdullah Karaaslanli , Bisakh Banerjee , Tapabrata Maiti , Selin Aviyente