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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

We consider the problem of learning causal networks with interventions, when each intervention is limited in size under Pearl's Structural Equation Model with independent errors (SEM-IE). The objective is to minimize the number of…

Artificial Intelligence · Computer Science 2015-11-03 Karthikeyan Shanmugam , Murat Kocaoglu , Alexandros G. Dimakis , Sriram Vishwanath

String diagrams are a powerful tool for reasoning about physical processes, logic circuits, tensor networks, and many other compositional structures. The distinguishing feature of these diagrams is that edges need not be connected to…

Category Theory · Mathematics 2010-11-19 Lucas Dixon , Aleks Kissinger

We introduce the class of interval $H$-graphs, which is the generalization of interval graphs, particularly interval bigraphs. For a fixed graph $H$ with vertices $a_1,a_2,\dots,a_k$, we say that an input graph $G$ with given partition…

Discrete Mathematics · Computer Science 2025-03-04 Haiko Müller , Arash Rafiey

The existence of Hamiltonian cycles in 1-planar graphs with higher connectivity has attracted considerable attention. Recently, the authors and Dong proved that 4-connected 1-planar chordal graphs are Hamiltonian-connected. In this paper,…

Combinatorics · Mathematics 2024-11-05 Licheng Zhang , Shengxiang Lv , Yuanqiu Huang

For a finite graph, a spectral curve is constructed as the zero set of a two-variate polynomial with integer coefficients coming from p-adic diffusion on the graph. It is shown that certain spectral curves can distinguish non-isomorphic…

Spectral Theory · Mathematics 2025-01-07 Patrick Erik Bradley , Ángel Morán Ledezma

The increasing prevalence of graph-structured data across various domains has intensified greater interest in graph classification tasks. While numerous sophisticated graph learning methods have emerged, their complexity often hinders…

Machine Learning · Computer Science 2025-09-03 Saiful Islam , Md. Nahid Hasan , Pitambar Khanra

We introduce a new model for investigating spectral properties of quantum graphs, a quantum circulant graph. Circulant graphs are the Cayley graphs of cyclic groups. Quantum circulant graphs with standard vertex conditions maintain…

Mathematical Physics · Physics 2019-06-21 JM Harrison , E Swindle

A chordal graph is a graph with no induced cycles of length at least $4$. Let $f(n,m)$ be the maximal integer such that every graph with $n$ vertices and $m$ edges has a chordal subgraph with at least $f(n,m)$ edges. In 1985 Erd\H{o}s and…

Combinatorics · Mathematics 2023-03-13 Lior Gishboliner , Benny Sudakov

In this paper we define signless Laplacian matrix of a hypergraph and obtain structural properties from its eigenvalues. We generalize several known results for graphs, relating the spectrum of this matrix with structural parameters of the…

Spectral Theory · Mathematics 2024-08-12 Kauê Cardoso , Vilmar Trevisan

In this work, we introduce the \emph{interval permutation segment (IP-SEG)} model that naturally generalizes the geometric intersection models of interval and permutation graphs. We study properties of two graph classes that arise from the…

Discrete Mathematics · Computer Science 2019-08-29 Zlatko Joveski , Jeremy P. Spinrad

In this book authors for the first time introduce the notion of strong neutrosophic graphs. They are very different from the usual graphs and neutrosophic graphs. Using these new structures special subgraph topological spaces are defined.…

Artificial Intelligence · Computer Science 2016-11-03 W. B. Vasantha Kandasamy , Ilanthenral K , Florentin Smarandache

In social networks the {\sc Strong Triadic Closure} is an assignment of the edges with strong or weak labels such that any two vertices that have a common neighbor with a strong edge are adjacent. The problem of maximizing the number of…

Data Structures and Algorithms · Computer Science 2016-10-10 Athanasios Konstantinidis , Charis Papadopoulos

Let $B=(X,Y,E)$ be a bipartite graph. A half-square of $B$ has one color class of $B$ as vertex set, say $X$; two vertices are adjacent whenever they have a common neighbor in $Y$. Every planar graph is a half-square of a planar bipartite…

Discrete Mathematics · Computer Science 2018-04-18 Hoang-Oanh Le , Van Bang Le

The spectral theory of the normalized Laplacian for chemical hypergraphs is further investigated. The signless normalized Laplacian is introduced and it is shown that its spectrum for classical hypergraphs coincides with the spectrum of the…

Combinatorics · Mathematics 2022-11-09 Eleonora Andreotti , Raffaella Mulas

We analyse properties of geometric intersection graphs to show the strict containment between some natural classes of geometric intersection graphs. In particular, we show the following properties: - A graph $G$ is outerplanar if and only…

Combinatorics · Mathematics 2017-02-02 Sergio Cabello , Miha Jejčič

Construction of non-isomorphic cospectral graphs is a nontrivial problem in spectral graph theory specially for large graphs. In this paper, we establish that graph theoretical partial transpose of a graph is a potential tool to create…

Combinatorics · Mathematics 2018-08-13 Supriyo Dutta , Bibhas Adhikari

A class $\mathcal{G}$ of graphs is hereditary if it is closed under taking induced subgraphs. We investigate the edge-add class, $\mathcal{G}^{\mathrm{add}}$, consisting of graphs that can be made members of $\mathcal{G}$ by adding at most…

Combinatorics · Mathematics 2026-04-10 Jagdeep Singh , Vaidy Sivaraman

We characterize which local matrix structures saturate Weyl's eigenvalue perturbation bound for graph Laplacians under geometrically constrained vertex displacements. Geometric graphs with heavy-tailed vertex noise arise across sensor…

Spectral Theory · Mathematics 2026-04-17 Ben Cardoen , Jeremy Budd , Enrico Amico , Ghassan Hamarneh , Fabian Spill

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
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