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相关论文: Evolving Networks and Birth-and-Death Processes

200 篇论文

The ever-increasing knowledge of the structure of various real-world networks has uncovered their complex multi-mechanism-governed evolution processes. Therefore, a better understanding of the structure and evolution of these networked…

物理与社会 · 物理学 2007-05-23 Ke Deng , Heping Zhao , Dejun Li

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…

统计力学 · 物理学 2007-05-23 M. Baiesi , S. S. Manna

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…

统计力学 · 物理学 2009-11-07 S. Valverde , R. Ferrer i Cancho , R. V. Sole

Many biological networks have been labelled scale-free as their degree distribution can be approximately described by a powerlaw distribution. While the degree distribution does not summarize all aspects of a network it has often been…

分子网络 · 定量生物学 2007-05-23 M. P. H. Stumpf , P. J. Ingram , I. Nouvel , C. Wiuf

We define a dynamic model of random networks, where new vertices are connected to old ones with a probability proportional to a sublinear function of their degree. We first give a strong limit law for the empirical degree distribution, and…

概率论 · 数学 2008-07-31 Steffen Dereich , Peter Morters

Preferential attachment is often suggested to be the underlying mechanism of the growth of a network, largely due to that many real networks are, to a certain extent, scale-free. However, such attribution is usually made under debatable…

应用统计 · 统计学 2025-09-16 Clement Lee

We propose a geometric growth model for weighted scale-free networks, which is controlled by two tunable parameters. We derive exactly the main characteristics of the networks, which are partially determined by the parameters. Analytical…

物理与社会 · 物理学 2011-11-09 Zhongzhi Zhang , Shuigeng Zhou , Lichao Chen , Jihong Guan , Lujun Fang , Yichao Zhang

We introduce a simple one-parameter network growth algorithm which is able to reproduce a wide variety of realistic network structures but without having to invoke any global information about node degrees such as preferential-attachment…

统计力学 · 物理学 2007-05-23 David M. D. Smith , Chiu Fan Lee , Neil F. Johnson

We study the growth of random networks under a constraint that the diameter, defined as the average shortest path length between all nodes, remains approximately constant. We show that if the graph maintains the form of its degree…

统计力学 · 物理学 2007-05-23 Rajan M. Lukose , Lada A. Adamic

We investigate the contact process on four different types of scale-free inhomogeneous random graphs evolving according to a stationary dynamics, where each potential edge is updated with a rate depending on the strength of the adjacent…

概率论 · 数学 2022-06-03 Emmanuel Jacob , Amitai Linker , Peter Mörters

We propose a simple dynamical model that generates networks with power-law degree distributions with the exponent 2 through rewiring only. At each time step, two nodes, i and j, are randomly selected, and one incoming link to i is…

统计力学 · 物理学 2012-04-27 Suhan Ree

Biological networks exhibit intricate architectures deemed to be crucial for their functionality. In particular, gene regulatory networks, which play a key role in information processing in the cell, display non-trivial architectural…

物理与社会 · 物理学 2020-02-13 Pablo Villegas , Miguel A. Muñoz , Juan A. Bonachela

Many social and biological networks consist of communities - groups of nodes within which connections are dense, but between which connections are sparser. Recently, there has been considerable interest in designing algorithms for detecting…

物理与社会 · 物理学 2009-11-11 Chunguang Li , Philip K. Maini

The origin of scale-free degree distributions in the context of networks is addressed through an analogous non-network model in which the node degree corresponds to the number of balls in a box and the rewiring of links to balls moving…

统计力学 · 物理学 2011-11-09 Petter Minnhagen , Sebastian Bernhardsson , Beom Jun Kim

The Internet, as well as many other networks, has a very complex connectivity recently modeled by the class of scale-free networks. This feature, which appears to be very efficient for a communications network, favors at the same time the…

统计力学 · 物理学 2009-10-31 Romualdo Pastor-Satorras , Alessandro Vespignani

We propose a growing network model that consists of two tunable mechanisms: growth by merging modules which are represented as complete graphs and a fitness-driven preferential attachment. Our model exhibits the three prominent statistical…

分子网络 · 定量生物学 2007-07-31 Kazuhiro Takemoto , Chikoo Oosawa

Connectivity correlations play an important role in the structure of scale-free networks. While several empirical studies exist, there is no general theoretical analysis that can explain the largely varying behavior of real networks. Here,…

物理与社会 · 物理学 2009-11-13 Lazaros K. Gallos , Chaoming Song , Hernan A. Makse

Scale-free networks are abundant in nature and society, describing such diverse systems as the world wide web, the web of human sexual contacts, or the chemical network of a cell. All models used to generate a scale-free topology are…

统计力学 · 物理学 2009-11-07 Albert-Laszlo Barabasi , Erzsebet Ravasz , Tamas Vicsek

We present a general model for the growth of weighted networks in which the structural growth is coupled with the edges' weight dynamical evolution. The model is based on a simple weight-driven dynamics and a weights' reinforcement…

统计力学 · 物理学 2009-11-10 Alain Barrat , Marc Barthelemy , Alessandro Vespignani

We discuss how various models of scale-free complex networks approach their limiting properties when the size N of the network grows. We focus mainly on equilibrated networks and their finite-size degree distributions. Our results show that…

统计力学 · 物理学 2009-11-13 B. Waclaw , L. Bogacz , W. Janke