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Many real-world networks have properties of small-world networks, with clustered local neighborhoods and low average-shortest path (ASP). They may also show a scale-free degree distribution, which can be generated by growth and preferential…

Statistical Mechanics · Physics 2007-05-23 Marcus Kaiser , Claus C. Hilgetag

Random networks with complex topology are common in Nature, describing systems as diverse as the world wide web or social and business networks. Recently, it has been demonstrated that most large networks for which topological information…

Disordered Systems and Neural Networks · Physics 2016-08-31 Albert-Laszlo Barabasi , Reka Albert , Hawoong Jeong

Networks are structures that pervade many natural and man-made phenomena. Recent findings have characterized many networks as not random structures, but as efficent complex formations. Current research has examined complex networks as…

Disordered Systems and Neural Networks · Physics 2007-05-23 Sean P. Gorman , Rajendra Kulkarni

We define the intrinsic scale at which a network begins to reveal its identity as the scale at which subgraphs in the network (created by a random walk) are distinguishable from similar sized subgraphs in a perturbed copy of the network. We…

Social and Information Networks · Computer Science 2019-01-29 Malik Magdon-Ismail , Kshiteesh Hegde

Small-world architectures may be implicated in a range of phenomena from disease propagation to networks of neurons in the cerebral cortex. While most of the recent attention on small-world networks has focussed on the effect of introducing…

Disordered Systems and Neural Networks · Physics 2007-05-23 Rajesh Kasturirangan

A large number of complex networks, both natural and artificial, share the presence of highly heterogeneous, scale-free degree distributions. A few mechanisms for the emergence of such patterns have been suggested, optimization not being…

Statistical Mechanics · Physics 2009-11-07 S. Valverde , R. Ferrer i Cancho , R. V. Sole

Real world networks have, for a long time, been modelled by scale-free networks, which have many sparsely connected nodes and a few highly connected ones (the hubs). However, both in society and in biology, a new structure must be…

Adaptation and Self-Organizing Systems · Physics 2019-05-10 R. Vilela Mendes

We study the properties of random graphs where for each vertex a {\it neighbourhood} has been previously defined. The probability of an edge joining two vertices depends on whether the vertices are neighbours or not, as happens in Small…

Disordered Systems and Neural Networks · Physics 2009-11-10 Sebastian Risau-Gusman

Small world models are networks consisting of many local links and fewer long range `shortcuts'. In this paper, we consider some particular instances, and rigorously investigate the distribution of their inter--point network distances. Our…

Disordered Systems and Neural Networks · Physics 2007-05-23 A. D. Barbour , Gesine Reinert

Community structures have been identified in various complex real-world networks, for example, communication, information, internet and shareholder networks. The scaling of community size distribution indicates the heterogeneity in the…

Physics and Society · Physics 2022-07-11 Qing Yao , Bingsheng Chen , Tim S. Evans , Kim Christensen

Here we analyze the topology of the network formed by the minima and transition states on the potential energy landscape of small clusters. We find that this network has both a small-world and scale-free character. In contrast to other…

Condensed Matter · Physics 2007-05-23 Jonathan P. K. Doye

Complex networks are characterized by several topological properties: degree distribution, clustering coefficient, average shortest path length, etc. Using a simple model to generate scale-free networks embedded on geographical space, we…

Disordered Systems and Neural Networks · Physics 2013-11-20 Satoru Morita

We describe the structure of the graphs with the smallest average distance and the largest average clustering given their order and size. There is usually a unique graph with the largest average clustering, which at the same time has the…

Molecular Networks · Quantitative Biology 2010-07-28 Dionysios Barmpoutis , Richard M. Murray

We analyze about two hundred naturally occurring networks with distinct dynamical origins to formally test whether the commonly assumed hypothesis of an underlying scale-free structure is generally viable. This has recently been questioned…

This study introduces an algorithm that generates undirected graphs with three main characteristics of real-world networks: scale-freeness, short distances between nodes (small-world phenomenon), and large clustering coefficients. The main…

Social and Information Networks · Computer Science 2025-02-27 João Pedro C. Morais , Ruben Interian

The small-world phenomenon in complex networks has been identified as being due to the presence of long-range links, i.e., links connecting nodes that would otherwise be separated by a long node-to-node distance. We find, surprisingly, that…

Disordered Systems and Neural Networks · Physics 2009-11-07 Adilson E. Motter , Takashi Nishikawa , Ying-Cheng Lai

Real growing networks like the WWW or personal connection based networks are characterized by a high degree of clustering, in addition to the small-world property and the absence of a characteristic scale. Appropriate modifications of the…

Statistical Mechanics · Physics 2009-11-07 Gabor Szabo , Mikko Alava , Janos Kertesz

The recently introduced Minimalist Model [Vazquez- Prada et al., 2002] of characteristic earthquakes provides a simple representation of the seismicity originated in a sin- gle fault. Here, we first characterize the properties of this model…

Adaptation and Self-Organizing Systems · Physics 2009-09-29 R. Lopez-Ruiz , M. Vazquez-Prada , J. B. Gomez , A. F. Pacheco

A number of recent studies have focused on the statistical properties of networked systems such as social networks and the World-Wide Web. Researchers have concentrated particularly on a few properties which seem to be common to many…

Statistical Mechanics · Physics 2009-11-07 Michelle Girvan , M. E. J. Newman

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
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