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We propose a novel paradigm for modeling real-world scale-free networks, where the integration of new nodes is driven by the combined attractiveness of degree and betweenness centralities, the competition of which (expressed by a parameter…

Physics and Society · Physics 2026-02-18 V. Adami , S. Emdadi-Mahdimahalleh , H. J. Herrmann , M. N. Najafi

Yang, Wang, and Motter [Phys. Rev. Lett. 109, 258701 (2012)] analyzed a model for network observability transitions in which a sensor placed on a node makes the node and the adjacent nodes observable. The size of the connected components…

Physics and Society · Physics 2013-10-17 Takehisa Hasegawa , Taro Takaguchi , Naoki Masuda

A network is formed using the $N$ sites of an one-dimensional lattice in the shape of a ring as nodes and each node with the initial degree $k_{in}=2$. $N$ links are then introduced to this network, each link starts from a distinct node,…

Statistical Mechanics · Physics 2009-11-07 G. Mukherjee , S. S. Manna

We study ensemble-based graph-theoretical methods aiming to approximate the size of the minimum dominating set (MDS) in scale-free networks. We analyze both analytical upper bounds of dominating sets and numerical realizations for…

Physics and Society · Physics 2014-09-23 F. Molnár , N. Derzsy , É. Czabarka , L. Székely , B. K. Szymanski , G. Korniss

We investigate analytically and numerically the dynamical properties of critical Boolean networks with power-law in-degree distributions. When the exponent of the in-degree distribution is larger than 3, we obtain results equivalent to…

Disordered Systems and Neural Networks · Physics 2009-11-13 Barbara Drossel , Florian Greil

We study the influence of elements diffusing in and out of a network to the topological changes of the network and characterize it by investigating the behavior of probability of degree distribution ($\Gamma(k)$) with degree $k$. The local…

Computational Physics · Physics 2011-09-02 Ravins , R. K. Brojen Singh

Probabilistic networks display a wide range of high average clustering coefficients independent of the number of nodes in the network. In particular, the local clustering coefficient decreases with the degree of the subtending node in a…

Physics and Society · Physics 2013-11-26 Vijay K Samalam

Learning the network structure underlying data is an important problem in machine learning. This paper introduces a novel prior to study the inference of scale-free networks, which are widely used to model social and biological networks.…

Machine Learning · Computer Science 2015-06-19 Qingming Tang , Siqi Sun , Jinbo Xu

We explore the possibility to interpret as a 'gas' the dynamical self-organized scale-free network recently introduced by Kim et al (2005). The role of 'momentum' of individual nodes is played by the degree of the node, the 'configuration…

Other Condensed Matter · Physics 2009-11-11 Stefan Thurner , Constantino Tsallis

Many complex systems--from social and communication networks to biological networks and the Internet--are thought to exhibit scale-free structure. However, prevailing explanations rely on the constant addition of new nodes, an assumption…

Adaptation and Self-Organizing Systems · Physics 2022-11-10 Christopher W. Lynn , Caroline M. Holmes , Stephanie E. Palmer

This paper introduces a method to generate hierarchically modular networks with prescribed node degree list by link switching. Unlike many existing network generating models, our method does not use link probabilities to achieve modularity.…

Other Computer Science · Computer Science 2009-07-05 Susan Khor

A general random graph evolution mechanism is defined. The evolution is a combination of the preferential attachment model and the interaction of N vertices (N>=3). A vertex in the graph is characterized by its degree and its weight. The…

Probability · Mathematics 2013-09-18 István Fazekas , Bettina Porvázsnyik

Network embedding aims to learn the low-dimensional representations of vertexes in a network, while structure and inherent properties of the network is preserved. Existing network embedding works primarily focus on preserving the…

Social and Information Networks · Computer Science 2017-11-30 Rui Feng , Yang Yang , Wenjie Hu , Fei Wu , Yueting Zhuang

We introduce two practical properties of hierarchical clustering methods for (possibly asymmetric) network data: excisiveness and linear scale preservation. The latter enforces imperviousness to change in units of measure whereas the former…

Machine Learning · Computer Science 2016-07-22 Gunnar Carlsson , Facundo Mémoli , Alejandro Ribeiro , Santiago Segarra

A scale-free network is grown in the Euclidean space with a global directional bias. On a vertical plane, nodes are introduced at unit rate at randomly selected points and a node is allowed to be connected only to the subset of nodes which…

Statistical Mechanics · Physics 2009-11-10 S. S. Manna , G. Mukherjee , Parongama Sen

We propose a model for growing networks based on a finite memory of the nodes. The model shows stylized features of real-world networks: power law distribution of degree, linear preferential attachment of new links and a negative…

Condensed Matter · Physics 2009-11-07 Konstantin Klemm , Victor M. Eguiluz

We show that the collapsed globular phase of a polymer accommodates a scale-free incompatibility graph of its contacts. The degree distribution of this network is found to decay with the exponent $\gamma = 1/(2-c)$ up to a cut-off degree…

Statistical Mechanics · Physics 2009-11-10 A. Kabakcioglu , A. L. Stella

We consider a system hierarchically modular, if besides its hierarchical structure it shows a sequence of scale separations from the point of view of some functionality or property. Starting from regular, deterministic objects like the…

Statistical Mechanics · Physics 2016-08-31 David Nagy , Gergely Tibely , Janos Kertesz

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

We study scale-free networks constructed via a cooperative Achlioptas growth process. Links between nodes are introduced in the network in order to produce a scale-free graph with given exponent lambda for the degree distribution, but the…

Physics and Society · Physics 2009-10-13 Filippo Radicchi , Santo Fortunato