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Exact maximum clique finders have progressed to the point where we can investigate cliques in million-node social and information networks, as well as find strongly connected components in temporal networks. We use one such finder to study…

Social and Information Networks · Computer Science 2012-10-31 Ryan A. Rossi , David F. Gleich , Assefaw H. Gebremedhin , Md. Mostofa Ali Patwary

A graph is $k$-clique-extendible if there is an ordering of the vertices such that whenever two $k$-sized overlapping cliques $A$ and $B$ have $k-1$ common vertices, and these common vertices appear between the two vertices $a,b\in…

Data Structures and Algorithms · Computer Science 2020-07-14 Mathew Francis , Rian Neogi , Venkatesh Raman

Let $G = (V,E)$ be a connected directed graph on $n$ vertices. Assign values from the set $\{1,2,\dots,n\}$ to the vertices of $G$ and update the values according to the following rule: uniformly at random choose a vertex and update its…

Data Structures and Algorithms · Computer Science 2024-06-05 John Larkin

A \emph{resolving set} $R$ in a graph $G$ is a set of vertices such that every vertex of $G$ is uniquely identified by its distances to the vertices of $R$. Introduced in the 1970s, this concept has been since then extensively studied from…

Combinatorics · Mathematics 2024-12-05 Jan Bok , Antoine Dailly , Tuomo Lehtilä

For a given graph $H$, its subdivisions carry the same topological structure. The existence of $H$-subdivisions within a graph $G$ has deep connections with topological, structural and extremal properties of $G$. One prominent example of…

Combinatorics · Mathematics 2023-08-22 Seonghyuk Im , Jaehoon Kim , Younjin Kim , Hong Liu

In the binomial random graph $\mathcal{G}(n,p)$, when $p$ changes from $(1-\varepsilon)/n$ (subcritical case) to $1/n$ and then to $(1+\varepsilon)/n$ (supercritical case) for $\varepsilon>0$, with high probability the order of the largest…

Combinatorics · Mathematics 2018-10-19 Oliver Cooley , Wenjie Fang , Nicola Del Giudice , Mihyun Kang

We study the asymptotic behavior of the clique number in rank-1 inhomogeneous random graphs, where edge probabilities between vertices are roughly proportional to the product of their vertex weights. We show that the clique number is…

Probability · Mathematics 2020-08-31 Kay Bogerd , Rui M. Castro , Remco van der Hofstad

For the Erd\H{o}s-R\'enyi random graph G(n,p), we give a precise asymptotic formula for the size of a largest vertex subset in G(n,p) that induces a subgraph with average degree at most t, provided that p = p(n) is not too small and t =…

Combinatorics · Mathematics 2013-09-04 Nikolaos Fountoulakis , Ross J. Kang , Colin McDiarmid

In this work we consider \emph{temporal networks}, i.e. networks defined by a \emph{labeling} $\lambda$ assigning to each edge of an \emph{underlying graph} $G$ a set of \emph{discrete} time-labels. The labels of an edge, which are natural…

Discrete Mathematics · Computer Science 2018-07-02 George B. Mertzios , Othon Michail , Paul G. Spirakis

Let $\alpha(G)$ and $\beta(G)$, denote the size of a largest independent set and the clique cover number of an undirected graph $G$. Let $H$ be an interval graph with $V(G)=V(H)$ and $E(G)\subseteq E(H)$, and let $\phi(G,H)$ denote the…

Combinatorics · Mathematics 2015-04-21 Farhad Shahrokhi

A temporal network is a mathematical way of precisely representing a time varying relationship among a group of agents. In this paper, we introduce the notion of $(\Delta, \gamma)$-Cliques of a temporal network, where every pair of vertices…

Data Structures and Algorithms · Computer Science 2018-05-01 Suman Banerjee , Bithika Pal

Many real-world networks evolve over time, that is, new contacts appear and old contacts may disappear. They can be modeled as temporal graphs where interactions between vertices (which represent people in the case of social networks) are…

Data Structures and Algorithms · Computer Science 2019-07-29 Matthias Bentert , Anne-Sophie Himmel , Hendrik Molter , Marco Morik , Rolf Niedermeier , René Saitenmacher

We find asymptotics of the maximum size of a chordal subgraph in a binomial random graph $G(n,p)$, for $p=\mathrm{const}$ and $p=n^{-\alpha+o(1)}$.

Combinatorics · Mathematics 2024-11-20 Michael Krivelevich , Maksim Zhukovskii

We consider a model for random hypergraphs with identifiability, an analogue of connectedness. This model has a phase transition in the proportion of identifiable vertices when the underlying random graph becomes critical. The phase…

Probability · Mathematics 2007-05-23 Christina Goldschmidt

Erd\H{o}s determined the maximum size of a nonhamiltonian graph of order $n$ and minimum degree at least $k$ in 1962. Recently, Ning and Peng generalized. Erd\H{o}s' work and gave the maximum size $h(n,c,k)$ of graphs with prescribed order…

Combinatorics · Mathematics 2021-12-06 Leilei Zhang

The well-known Erd\H{o}s-Hajnal conjecture states that for any graph $F$, there exists $\epsilon>0$ such that every $n$-vertex graph $G$ that contains no induced copy of $F$ has a homogeneous set of size at least $n^{\epsilon}$. We consider…

Combinatorics · Mathematics 2023-05-03 Maria Axenovich , Domagoj Bradač , Lior Gishboliner , Dhruv Mubayi , Lea Weber

A $d$-regular graph on $n$ nodes has at most $T_{\max} = \frac{n}{3} \tbinom{d}{2}$ triangles. We compute the leading asymptotics of the probability that a large random $d$-regular graph has at least $c \cdot T_{\max}$ triangles, and…

Combinatorics · Mathematics 2021-04-16 Pim van der Hoorn , Gabor Lippner , Elchanan Mossel

A clique colouring of a graph is a colouring of the vertices such that no maximal clique is monochromatic (ignoring isolated vertices). The least number of colours in such a colouring is the clique chromatic number. Given $n$ points $x_1,…

Combinatorics · Mathematics 2018-12-04 Colin McDiarmid , Dieter Mitsche , Pawel Pralat

This paper is interested in independent sets (or equivalently, cliques) in uniform random cographs. We also study their permutation analogs, namely, increasing subsequences in uniform random separable permutations. First, we prove that,…

In this work, we consider the application of continuous time quantum walking(CTQW) to the Maximum Clique(MC) Problem. Performing CTQW on graphs will generate distinct periodic probability amplitude for different vertices. We will show that…

Data Structures and Algorithms · Computer Science 2020-05-26 Xi Li , Mingyou Wu , Hanwu Chen
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