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We explore a systematic approach to studying the dynamics of evolving networks at a coarse-grained, system level. We emphasize the importance of finding good observables (network properties) in terms of which coarse grained models can be…

Small-world networks are ubiquitous in real-life systems. Most previous models of small-world networks are stochastic. The randomness makes it more difficult to gain a visual understanding on how do different nodes of networks interact with…

Statistical Mechanics · Physics 2007-05-23 Zhongzhi Zhang , Lili Rong , Chonghui Guo

Growing synthetic networks that follow power law distributions of a node's degree often involves adding one node at a time. Each node is added to the network with a fixed amount of edges and those edges are frozen for all future time steps.…

Physics and Society · Physics 2026-01-27 Justin Downes

We propose a model of network growth in which the network is co-evolving together with the dynamics of a quantum mechanical system, namely a quantum walk taking place over the network. The model naturally generalizes the Barab\'{a}si-Albert…

Numerous concise models such as preferential attachment have been put forward to reveal the evolution mechanisms of real-world networks, which show that real-world networks are usually jointly driven by a hybrid mechanism of multiplex…

Physics and Society · Physics 2016-01-12 Qian-Ming Zhang , Xiao-Ke Xu , Yu-Xiao Zhu , Tao Zhou

Many complex networks from the World-Wide-Web to biological networks are growing taking into account the heterogeneous features of the nodes. The feature of a node might be a discrete quantity such as a classification of a URL document as…

Physics and Society · Physics 2013-05-30 Luca Ferretti , Michele Cortelezzi , Bin Yang , Giacomo Marmorini , Ginestra Bianconi

Adaptive networks are a novel class of dynamical networks whose topologies and states coevolve. Many real-world complex systems can be modeled as adaptive networks, including social networks, transportation networks, neural networks and…

Social and Information Networks · Computer Science 2017-05-29 Hiroki Sayama , Irene Pestov , Jeffrey Schmidt , Benjamin James Bush , Chun Wong , Junichi Yamanoi , Thilo Gross

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…

Probability · Mathematics 2008-07-31 Steffen Dereich , Peter Morters

A key problem in the study and design of complex systems is the apparent disconnection between the microscopic and the macroscopic. It is not straightforward to identify the local interactions that give rise to an observed global…

Adaptation and Self-Organizing Systems · Physics 2016-06-28 H. Silk , M. Homer , T. Gross

We consider a one-dimensional network in which the nodes at Euclidean distance $l$ can have long range connections with a probabilty $P(l) \sim l^{-\delta}$ in addition to nearest neighbour connections. This system has been shown to exhibit…

Statistical Mechanics · Physics 2009-11-07 Parongama Sen , Kinjal Banerjee , Turbasu Biswas

Ever since the Barab\'{a}si-Albert (BA) scale-free network has been proposed, network modeling has been studied intensively in light of the network growth and the preferential attachment (PA). However, numerous real systems are featured…

Social and Information Networks · Computer Science 2025-11-25 Yuhan Li , Minyu Feng , Jürgen Kurths

Complex networks have abundant and extensive applications in real life. Recently, researchers have proposed a number of complex networks, in which some are deterministic and others are random. Compared with deterministic networks, random…

Physics and Society · Physics 2020-11-02 Xiaomin Wang , Fei Ma

Statistical significance of network clustering has been an unresolved problem since it was observed that community detection algorithms produce false positives even in random graphs. After a phase transition between undetectable and…

Social and Information Networks · Computer Science 2016-05-03 Jeremi K. Ochab

Navigability, an ability to find a logarithmically short path between elements using only local information, is one of the most fascinating properties of real-life networks. However, the exact mechanism responsible for the formation of…

Physics and Society · Physics 2016-07-26 Yury A. Malkov , Alexander Ponomarenko

It has been shown that many networks associated with complex systems are small-world (they have both a large local clustering coefficient and a small diameter) and they are also scale-free (the degrees are distributed according to a power…

Social and Information Networks · Computer Science 2016-05-25 L. Barrière , F. Comellas , C. Dalfó , M. A. Fiol

Networks grow and evolve by local events, such as the addition of new nodes and links, or rewiring of links from one node to another. We show that depending on the frequency of these processes two topologically different networks can…

Disordered Systems and Neural Networks · Physics 2009-10-31 Reka Albert , Albert-Laszlo Barabasi

We consider the observability model in networks with arbitrary topologies. We introduce a system of coupled nonlinear equations, valid under the locally tree-like ansatz, to describe the size of the largest observable cluster as a function…

Physics and Society · Physics 2016-09-28 Yang Yang , Filippo Radicchi

In this paper, we study the clustering properties of the Spatial Preferential Attachment (SPA) model. This model naturally combines geometry and preferential attachment using the notion of spheres of influence. It was previously shown in…

Probability · Mathematics 2019-06-04 Lenar Iskhakov , Bogumil Kaminski , Maksim Mironov , Pawel Pralat , Liudmila Prokhorenkova

Systems as diverse as genetic networks or the world wide web are best described as networks with complex topology. A common property of many large networks is that the vertex connectivities follow a scale-free power-law distribution. This…

Disordered Systems and Neural Networks · Physics 2015-06-25 Albert-Laszlo Barabasi , Reka Albert

We evolve network topology of an asymmetrically connected threshold network by a simple local rewiring rule: quiet nodes grow links, active nodes lose links. This leads to convergence of the average connectivity of the network towards the…

Disordered Systems and Neural Networks · Physics 2009-10-31 Stefan Bornholdt , Thimo Rohlf