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We introduce a deterministic model for scale-free networks, whose degree distribution follows a power-law with the exponent $\gamma$. At each time step, each vertex generates its offsprings, whose number is proportional to the degree of…

Statistical Mechanics · Physics 2009-11-07 S. Jung , S. Kim , B. Kahng

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 investigate analytically and numerically the critical line in undirected random Boolean networks with arbitrary degree distributions, including scale-free topology of connections $P(k)\sim k^{-\gamma}$. We show that in infinite…

Disordered Systems and Neural Networks · Physics 2013-05-29 Piotr Fronczak , Agata Fronczak , Janusz A. Holyst

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

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

We study a modified version of a model previously proposed by Jackson and Wolinsky to account for communicating information and allocating goods in socioeconomic networks. In the model, the utility function of each node is given by a…

Physics and Society · Physics 2009-11-13 Rui Carvalho , Giulia Iori

Extensive studies have been done to understand the principles behind architectures of real networks. Recently, evidences for hierarchical organization in many real networks have also been reported. Here, we present a new hierarchical model…

Other Condensed Matter · Physics 2007-05-23 J. C. Nacher , N. Ueda , M. Kanehisa , T. Akutsu

Most of various large-size complex systems in nature and society can be well described as complex networks (graphs) to better understand the evolutional mechanisms and dynamical functions behind themselves. Of some part follow scale-free…

Physics and Society · Physics 2023-08-08 Fei Ma

Funnelling effect, in the context of searching on networks, precisely indicates that the search takes place through a few specific nodes. We define the funnelling capacity $f$ of a node as the fraction of successful dynamic paths through it…

Physics and Society · Physics 2015-05-13 Parongama Sen

We bring rigor to the vibrant activity of detecting power laws in empirical degree distributions in real-world networks. We first provide a rigorous definition of power-law distributions, equivalent to the definition of regularly varying…

Physics and Society · Physics 2019-10-23 Ivan Voitalov , Pim van der Hoorn , Remco van der Hofstad , Dmitri Krioukov

Using a steady state process of node duplication and deletion we produce networks with 1/k scale-free degree distributions in the limit of vanishing connectance. This occurs even though there is no growth involved and inherent preferential…

Statistical Mechanics · Physics 2007-05-23 Simon Laird , Henrik Jeldtoft Jensen

A random network is grown by introducing at unit rate randomly selected nodes on the Euclidean space. A node is randomly connected to its $i$-th predecessor of degree $k_i$ with a directed link of length $\ell$ using a probability…

Statistical Mechanics · Physics 2009-11-07 S. S. Manna , Parongama Sen

We propose a network description of large market investments, where both stocks and shareholders are represented as vertices connected by weighted links corresponding to shareholdings. In this framework, the in-degree ($k_{in}$) and the sum…

Statistical Mechanics · Physics 2009-02-06 Diego Garlaschelli , Stefano Battiston , Maurizio Castri , Vito D. P. Servedio , Guido Caldarelli

The degree distributions of many real world networks follow power-laws whose exponents tend to fall between two and three. Within the framework of the Barabasi-Albert model (BA model), we explain this empirical observation by a simple fact.…

Physics and Society · Physics 2009-05-19 Shinji Tanimoto

We study the condensation phenomenon in a zero range process on scale-free networks. We show that the stationary state property depends only on the degree distribution of underlying networks. The model displays a stationary state phase…

Statistical Mechanics · Physics 2007-05-23 Jae Dong Noh

We propose and study a model of weighted scale-free networks incorporating a stochastic scheme for weight assignments to the links, taking into account both the popularity and fitness of a node. As the network grows the weights of links are…

Statistical Mechanics · Physics 2009-11-10 Dafang Zheng , Steffen Trimper , Bo Zheng , P. M. Hui

A network is scale-free if its connectivity density function is proportional to a power-law distribution. Scale-free networks may provide an explanation for the robustness observed in certain physical and biological phenomena, since the…

Molecular Networks · Quantitative Biology 2018-07-03 Peter Clote

Activity or spin patterns on random scale-free network are studied by mean field analysis and computer simulations. These activity patterns evolve in time according to local majority-rule dynamics which is implemented using (i) parallel or…

Disordered Systems and Neural Networks · Physics 2007-05-23 Haijun Zhou , Reinhard Lipowsky

We study spatial networks constructed by randomly placing nodes on a manifold and joining two nodes with an edge whenever their distance is less than a certain cutoff. We derive the general expression for the connectivity distribution of…

Disordered Systems and Neural Networks · Physics 2009-11-10 Carl Herrmann , Marc Barthelemy , Paolo Provero