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Subgraphs and cycles are often used to characterize the local properties of complex networks. Here we show that the subgraph structure of real networks is highly time dependent: as the network grows, the density of some subgraphs remains…

Disordered Systems and Neural Networks · Physics 2009-11-11 Alexei Vazquez , Joao G. Oliveira , Albert-Laszlo Barabasi

Contrary to many recent models of growing networks, we present a model with fixed number of nodes and links, where it is introduced a dynamics favoring the formation of links between nodes with degree of connectivity as different as…

Statistical Mechanics · Physics 2007-05-23 M. Baiesi , S. S. Manna

The problem of defining a statistical ensemble of random graphs with an arbitrary connectivity distribution is discussed. Introducing such an ensemble is a step towards uderstanding the geometry of wide classes of graphs independently of…

Statistical Mechanics · Physics 2007-05-23 A. Krzywicki

We study scale free simple graphs with an exponent of the degree distribution $\gamma$ less than two. Generically one expects such extremely skewed networks -- which occur very frequently in systems of virtually or logically connected units…

Statistical Mechanics · Physics 2007-05-23 Hamed Seyed-allaei , Ginestra Bianconi , Matteo Marsili

Both empirical and theoretical investigations of scale-free network models have found that large degrees in a network exert an outsized impact on its structure. However, the tools used to infer the tail behavior of degree distributions in…

Statistics Theory · Mathematics 2024-10-31 Daniel Cirkovic , Tiandong Wang , Daren B. H. Cline

Extending several previous results we obtained nearly tight estimates on the maximum size of a clique-minor in various classes of expanding graphs. These results can be used to show that graphs without short cycles and other H-free graphs…

Combinatorics · Mathematics 2007-07-03 Michael Krivelevich , Benny Sudakov

Real-life networks often encounter vertex dysfunctions, which are usually followed by recoveries after appropriate maintenances. In this paper we present our research on a model of scale-free networks whose vertices are regularly removed…

Physics and Society · Physics 2013-10-08 Linjun Li , Xiangwen Wang

The theory of dense graph limits comes with a natural sampling process which yields an inhomogeneous variant G(n,W) of the Erdos-Renyi random graph. Here we study the clique number of these random graphs. We establish the concentration of…

Combinatorics · Mathematics 2018-12-04 Martin Doležal , Jan Hladký , András Máthé

We show how scale-free degree distributions can emerge naturally from growing networks by using random walks for selecting vertices for attachment. This result holds for several variants of the walk algorithm and for a wide range of…

Statistical Mechanics · Physics 2007-05-23 T. S. Evans , J. P. Saramaki

We study the behaviour of clique complexes of graphs under the operation of taking graph powers. As an example we compute the clique complexes of powers of cycles, or, in other words, the independence complexes of circular complete graphs.

Combinatorics · Mathematics 2015-03-19 Michal Adamaszek

We define a statistical ensemble of non-degenerate graphs, i.e. graphs without multiple- and self-connections between nodes. The node degree distribution is arbitrary, but the nodes are assumed to be uncorrelated. This completes our earlier…

Statistical Mechanics · Physics 2009-11-07 Z. Burda , A. Krzywicki

Methods connecting dynamical systems and graph theory have attracted increasing interest in the past few years, with applications ranging from a detailed comparison of different kinds of dynamics to the characterisation of empirical data.…

Statistical Mechanics · Physics 2018-01-18 Marcello A. Budroni , Andrea Baronchelli , Romualdo Pastor-Satorras

A general population evolution model is considered. Any individual of the population is characterized by its score. Certain general conditions are assumed concerning the number of the individuals and their scores. Asymptotic theorems are…

Probability · Mathematics 2016-04-07 I. Fazekas , Cs. Noszály , A. Perecsényi

A population of complete subgraphs or cliques in a network evolving via duplication-divergence is considered. We find that a number of cliques of each size scales linearly with the size of the network. We also derive a clique population…

Molecular Networks · Quantitative Biology 2009-11-11 I. Ispolatov , P. L. Krapivsky , I. Mazo , A. Yuryev

Cliques are defined as complete graphs or subgraphs; they are the strongest form of cohesive subgroup, and are of interest in both social science and engineering contexts. In this paper we show how to efficiently estimate the distribution…

Social and Information Networks · Computer Science 2013-08-16 Minas Gjoka , Emily Smith , Carter T. Butts

We study some percolation problems on the complete graph over $\mathbf N$. In particular, we give sharp sufficient conditions for the existence of (finite or infinite) cliques and paths in a random subgraph. No specific assumption on the…

Probability · Mathematics 2011-03-29 A. Berarducci , P. Majer , M. Novaga

Using a simple model with link removals as well as link additions, we show that an evolving network is scale free with a degree exponent in the range of (2, 4]. We then establish a relation between the network evolution and a set of…

Mathematical Physics · Physics 2007-05-23 Dinghua Shi , Liming Liu , Xiang Zhu , Huijie Zhou , Binbin Wang

In several scale free graph models the asymptotic degree distribution and the characteristic exponent change when only a smaller set of vertices is considered. Looking at the common properties of these models, we present sufficient…

Probability · Mathematics 2010-07-27 Agnes Backhausz , Tamas F. Mori

For uniform random permutations conditioned to have no long cycles, we prove that the total number of cycles satisfies a central limit theorem. Under additional assumptions on the asymptotic behavior of the set of allowed cycle lengths, we…

Probability · Mathematics 2016-08-31 Volker Betz , Helge Schäfer

We study the distribution of cycles of length h in large networks (of size N>>1) and find it to be an excellent ergodic estimator, even in the extreme inhomogeneous case of scale-free networks. The distribution is sharply peaked around a…

Disordered Systems and Neural Networks · Physics 2009-11-10 Hernan D. Rozenfeld , Joseph E. Kirk , Erik M. Bollt , Daniel ben-Avraham