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We study the limit theory of large threshold graphs and apply this to a variety of models for random threshold graphs. The results give a nice set of examples for the emerging theory of graph limits.

Combinatorics · Mathematics 2009-08-19 Persi Diaconis , Susan Holmes , Svante Janson

Graph coloring problems are a central topic of study in the theory of algorithms. We study the problem of partially coloring partially colorable graphs. For $\alpha \leq 1$ and $k \in \mathbb{Z}^+$, we say that a graph $G=(V,E)$ is…

Data Structures and Algorithms · Computer Science 2019-09-02 Suprovat Ghoshal , Anand Louis , Rahul Raychaudhury

Recently, variants of many classical extremal theorems have been proved in the random environment. We, complementing existing results, extend the Erd\H{o}s-Gallai Theorem in random graphs. In particular, we determine, up to a constant…

Combinatorics · Mathematics 2020-01-15 József Balogh , Andrzej Dudek , Lina Li

The problem of finding paths in temporal graphs has been recently considered due to its many applications. In this paper we consider a variant of the problem that, given a vertex-colored temporal graph, asks for a path whose vertices have…

Data Structures and Algorithms · Computer Science 2021-09-06 Riccardo Dondi , Mohammad Mehdi Hosseinzadeh

An incidence of a graph G is a pair (v, e) where v is a vertex of G and e is an edge of G incident with v. Two incidences (v, e) and (w, f) of G are adjacent whenever (i) v = w, or (ii) e = f , or (iii) vw = e or f. An incidence p-colouring…

Discrete Mathematics · Computer Science 2018-07-31 Brahim Benmedjdoub , Isma Bouchemakh , Eric Sopena , Â\' Sopena

The firefighter problem is defined as below. A fire initially breaks out at a vertex r on a graph G. In each step, a firefighter chooses to protect one vertex, which is not yet burnt. And the fire spreads out to its unprotected neighboring…

Data Structures and Algorithms · Computer Science 2015-03-19 Ming Lam Leung

In the random graph $G(n,p)$ with $pn$ bounded, the degrees of the vertices are almost i.i.d Poisson random variables with mean $\gl:= p(n-1)$. Motivated by this fact, we introduce the Poisson cloning model $G_{PC} (n,p)$ for random graphs…

Combinatorics · Mathematics 2008-05-28 Jeong Han Kim

The burning number of a graph can be used to measure the spreading speed of contagion in a network. The burning number conjecture is arguably the main unresolved conjecture related to this graph parameter, which can be settled by showing…

Combinatorics · Mathematics 2022-07-29 Ta Sheng Tan , Wen Chean Teh

The curling number of a graph G is defined as the number of times an element in the degree sequence of G appears the maximum. Graph colouring is an assignment of colours, labels or weights to the vertices or edges of a graph. A colouring…

General Mathematics · Mathematics 2018-04-06 C. Susanth , N. K. Sudev , S. J. Kalayathankal

The burning number $b(G)$ of a graph $G$ was introduced by Bonato, Janssen, and Roshanbin [Lecture Notes in Computer Science 8882 (2014)] for measuring the speed of the spread of contagion in a graph. They proved for any connected graph $G$…

Combinatorics · Mathematics 2016-06-27 Max Land , Linyuan Lu

Topics concerning metric dimension related invariants in graphs are nowadays intensively studied. This compendium of combinatorial and computational results on this topic is an attempt of surveying those contributions that are of the…

Combinatorics · Mathematics 2021-07-13 Dorota Kuziak , Ismael G. Yero

We study a graph parameter related to resolving sets and metric dimension, namely the resolving number, introduced by Chartrand, Poisson and Zhang. First, we establish an important difference between the two parameters: while computing the…

Combinatorics · Mathematics 2013-09-03 Delia Garijo , Antonio González , Alberto Márquez

Graph theory provides fundamental concepts for many fields of science like statistical physics, network analysis and theoretical computer science. Here we give a pedagogical introduction to graph theory, divided into three sections. In the…

Disordered Systems and Neural Networks · Physics 2007-05-23 Alexander K. Hartmann , Martin Weigt

Graph Neural Networks (GNNs) have achieved notable success in the analysis of non-Euclidean data across a wide range of domains. However, their applicability is constrained by the dependence on the observed graph structure. To solve this…

Machine Learning · Computer Science 2024-09-19 Ziyan Wang , Yaxuan He , Bin Liu

We show a method how to convert any graph into the binary number and vice versa. We derive upper bound for maximum number of graphs, that, have fixed number of vertices and can be colored with n colors (n is any given number). Proof for the…

Combinatorics · Mathematics 2007-05-23 Kamil Kulesza , Zbigniew Kotulski

Graph burning is motivated by the spread of social influence, and the burning number measures the speed of the spread. Given that the smallest burning number among the spanning trees of a graph determines the burning number of a connected…

Combinatorics · Mathematics 2025-07-01 Eugene Jun Tong Leong , Kai An Sim , Wen Chean Teh

In this paper we study graph burnings using methods of algebraic topology. We prove that the time function of a burning is a graph map to a path graph. Afterwards, we define a category whose objects are graph burnings and morphisms are…

Algebraic Topology · Mathematics 2024-07-08 Yuri Muranov , Anna Muranova

Aims. An attempt to classify gamma-ray bursts (GRBs) with a low level of supervision using the state-of-the-start approaches stemming from graph theory was undertaken. Methods. Graph-based classification methods, relying on different…

High Energy Astrophysical Phenomena · Physics 2021-09-28 Mariusz Tarnopolski

Correlations of active and passive random intersection graphs are studied in this letter. We present the joint probability generating function for degrees of $G^{active}(n,m,p)$ and $G^{passive}(n,m,p)$, which are generated by a random…

Combinatorics · Mathematics 2009-10-27 Yilun Shang

We propose and investigate a unifying class of sparse random graph models, based on a hidden coloring of edge-vertex incidences, extending an existing approach, Random graphs with a given degree distribution, in a way that admits a…

Statistical Mechanics · Physics 2009-11-10 Bo Söderberg
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