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We provide a simple proof that graphs in a general class of self-similar networks have zero percolation threshold. The considered self-similar networks include random scale-free graphs with given expected node degrees and zero clustering,…

Disordered Systems and Neural Networks · Physics 2011-01-28 M. Angeles Serrano , Dmitri Krioukov , Marian Boguna

We investigate a new width parameter, the fusion-width of a graph. It is a natural generalization of the tree-width, yet strong enough that not only graphs of bounded tree-width, but also graphs of bounded clique-width, trivially have…

Data Structures and Algorithms · Computer Science 2014-02-11 Martin Fürer

The topology of the Internet has typically been measured by sampling traceroutes, which are roughly shortest paths from sources to destinations. The resulting measurements have been used to infer that the Internet's degree distribution is…

Disordered Systems and Neural Networks · Physics 2013-05-29 Aaron Clauset , Cristopher Moore

We propose a simple random process inducing various types of random graphs and the scale free random graphs among others. The model is of a threshold nature and differs from the preferential attachment approach discussed in the literature…

Disordered Systems and Neural Networks · Physics 2007-05-23 D. Volchenkov , Ph. Blanchard

The clustering coefficient of a vertex in a graph is the proportion of neighbours of the vertex that are adjacent. The minimum clustering coefficient of a graph is the smallest clustering coefficient taken over all vertices. A complete…

Combinatorics · Mathematics 2016-01-08 Adam Borchert , Skylar Nicol , Ortrud R. Oellermann

What distribution of graphical degree sequence is invariant under ``scaling''? Are these graphs always power-law graphs? We show the answer is a surprising ``yes'' for sparse graphs if we ignore isolated vertices, or more generally, the…

Combinatorics · Mathematics 2007-05-23 Joshua N. Cooper , Lincoln Lu

We report on exact results for the degree $K$, the diameter $D$, the clustering coefficient $C$, and the betweenness centrality $B$ of a hierarchical network model with a replication factor $M$. Such quantities are calculated exactly with…

Statistical Mechanics · Physics 2009-11-07 Jae Dong Noh

Unlike the well-studied models of growing networks, where the dominant dynamics consist of insertions of new nodes and connections, and rewiring of existing links, we study {\em ad hoc} networks, where one also has to contend with rapid and…

Disordered Systems and Neural Networks · Physics 2009-11-10 Nima Sarshar , Vwani Roychowdhury

This paper studies the structure of graphs with given tree-width and excluding a fixed complete bipartite subgraph, which generalises the bounded degree setting. We give a new structural description of such graphs in terms of so-called…

Combinatorics · Mathematics 2025-12-15 Chun-Hung Liu , David R. Wood

We analyze the degree distribution's cut-off in finite size scale-free networks. We show that the cut-off behavior with the number of vertices $N$ is ruled by the topological constraints induced by the connectivity structure of the network.…

Disordered Systems and Neural Networks · Physics 2009-11-10 Marian Boguna , Romualdo Pastor-Satorras , Alessandro Vespignani

Many hard graph problems can be solved efficiently when restricted to graphs of bounded treewidth, and more generally to graphs of bounded clique-width. But there is a price to be paid for this generality, exemplified by the four problems…

Data Structures and Algorithms · Computer Science 2014-05-01 Sigve Hortemo Sæther , Jan Arne Telle

Recurrence networks are complex networks, constructed from time series data, having several practical applications. Though their properties when constructed with the threshold value \epsilon chosen at or just above the percolation threshold…

Chaotic Dynamics · Physics 2016-07-19 Rinku Jacob , K. P. Harikrishnan , R. Misra , G. Ambika

This work will appear as a chapter in a forthcoming volume titled "Topics in Probabilistic Graph Theory". A theory of scaling limits for random graphs has been developed in recent years. This theory gives access to the large-scale geometric…

Probability · Mathematics 2024-10-18 Louigi Addario-Berry , Christina Goldschmidt

Many real-world scale-free networks, such as neural networks and online communication networks, consist of a fixed number of nodes but exhibit dynamic edge fluctuations. However, traditional models frequently overlook scenarios where the…

Social and Information Networks · Computer Science 2026-04-02 Yichao Yao , Minyu Feng , Matjaž Perc , Jürgen Kurths

A central claim in modern network science is that real-world networks are typically "scale free," meaning that the fraction of nodes with degree $k$ follows a power law, decaying like $k^{-\alpha}$, often with $2 < \alpha < 3$. However,…

Physics and Society · Physics 2019-03-19 Anna D. Broido , Aaron Clauset

This Master's thesis examines the properties of large degree vertices in random recursive directed acyclic graphs (RRDAGs), a generalization of the well-studied random recursive tree (RRT) model. Using a novel adaptation of Kingman's…

Probability · Mathematics 2025-03-11 Rafael Engel

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

Very often, when studying topological or dynamical properties of random scale-free networks, it is tacitly assumed that degree-degree correlations are not present. However, simple constraints, such as the absence of multiple edges and…

Physics and Society · Physics 2016-03-23 J. B. de Brito , C. I. N. Sampaio Filho , A. A. Moreira , J. S. Andrade

In this paper, we propose a class of graphs $G^{\star}(m,t)$ and first study some structural properties, such as, average degree, on them. The results show that (1) graphs $G^{\star}(m,t)$ have density feature because of their average…

Physics and Society · Physics 2020-03-30 Fei Ma , Ping Wang

Recurrence networks are a novel tool of nonlinear time series analysis allowing the characterisation of higher-order geometric properties of complex dynamical systems based on recurrences in phase space, which are a fundamental concept in…

Chaotic Dynamics · Physics 2016-04-07 Y. Zou , J. Heitzig , R. V. Donner , J. F. Donges , J. D. Farmer , R. Meucci , S. Euzzor , N. Marwan , J. Kurths