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Related papers: Scale-free Segregation in Transport Networks

200 papers

Although traffic prediction has been receiving considerable attention with a number of successes in the context of intelligent transportation systems, the prediction of traffic states over a complex transportation network that contains…

Artificial Intelligence · Computer Science 2024-06-21 Zilin Bian , Jingqin Gao , Kaan Ozbay , Zhenning Li

We derive the finite size dependence of the clustering coefficient of scale-free random graphs generated by the configuration model with degree distribution exponent $2<\gamma<3$. Degree heterogeneity increases the presence of triangles in…

Disordered Systems and Neural Networks · Physics 2015-06-05 Pol Colomer-de-Simon , Marian Boguna

We describe an ensemble of growing scale-free networks in an equilibrium framework, providing insight into why the exponent of empirical scale-free networks in nature is typically robust. In an analogy to thermostatistics, to describe the…

Physics and Society · Physics 2014-06-11 João P. da Cruz , Nuno A. M. Araújo , Frank Raischel , Pedro G. Lind

Betweenness centrality lies at the core of both transport and structural vulnerability properties of complex networks, however, it is computationally costly, and its measurement for networks with millions of nodes is near impossible. By…

Physics and Society · Physics 2015-05-18 Maria Ercsey-Ravasz , Zoltan Toroczkai

We present simulation results for the contact process on regular, cubic networks that are composed of a one-dimensional lattice and a set of long edges with unbounded length. Networks with different sets of long edges are considered, that…

Statistical Mechanics · Physics 2015-05-13 R. Juhász , G. Ódor

We define gradient networks as directed graphs formed by local gradients of a scalar field distributed on the nodes of a substrate network G. We derive an exact expression for the in-degree distribution of the gradient network when the…

Disordered Systems and Neural Networks · Physics 2007-05-23 Zoltan Toroczkai , Balazs Kozma , Kevin E. Bassler , N. W. Hengartner , G. Korniss

In this paper we analyze the transport of passive tracers by deterministic stationary incompressible flows which can be decomposed over an infinite number of spatial scales without separation between them. It appears that a low order…

Mathematical Physics · Physics 2009-11-10 Houman Owhadi

Recently there have been a tremendous interest in models of networks with a power-law distribution of degree -- so called "scale-free networks." It has been observed that such networks, normally, have extremely short path-lengths, scaling…

Disordered Systems and Neural Networks · Physics 2007-05-23 Petter Holme

We show that not only preferential attachment but also preferential depletion leads to scale-free networks. The resulting degree distribution exponents is typically less than two (5/3) as opposed to the case of the growth models studied…

Physics and Society · Physics 2015-05-27 Christian M. Schneider , Lucilla de Arcangelis , Hans J. Herrmann

We analyze how the transient dynamics of large dynamical systems in the vicinity of a stationary point, modeled by a set of randomly coupled linear differential equations, depends on the network topology. We characterize the transient…

Adaptation and Self-Organizing Systems · Physics 2024-01-17 Wojciech Tarnowski , Izaak Neri , Pierpaolo Vivo

We study the statistical properties of the sampled scale-free networks, deeply related to the proper identification of various real-world networks. We exploit three methods of sampling and investigate the topological properties such as…

Disordered Systems and Neural Networks · Physics 2009-11-24 Sang Hoon Lee , Pan-Jun Kim , Hawoong Jeong

It was discovered a few years ago that many networks in the real world exhibit self-similarity. A lot of researches on the structures and processes on real and artificial fractal complex networks have been done, drawing an analogy to…

Statistical Mechanics · Physics 2014-02-06 Yoshihito Hotta

Optimal transportation distances are valuable for comparing and analyzing probability distributions, but larger-scale computational techniques for the theoretically favorable quadratic case are limited to smooth domains or regularized…

Other Computer Science · Computer Science 2016-03-23 Justin Solomon , Raif Rustamov , Leonidas Guibas , Adrian Butscher

In order to maintain consistent quality of service, computer network engineers face the task of monitoring the traffic fluctuations on the individual links making up the network. However, due to resource constraints and limited access, it…

Applications · Statistics 2010-05-26 Joel Vaughan , Stilian A. Stoev , George Michailidis

We develop a theoretical approach to percolation in random clustered networks. We find that, although clustering in scale-free networks can strongly affect some percolation properties, such as the size and the resilience of the giant…

Disordered Systems and Neural Networks · Physics 2009-11-11 M. Angeles Serrano , Marian Boguna

When we represent a network of sensors in Euclidean space by a graph, there are two distances between any two nodes that we may consider. One of them is the Euclidean distance. The other is the distance between the two nodes in the graph,…

Networking and Internet Architecture · Computer Science 2009-06-10 Rodrigo S. C. Leao , Valmir C. Barbosa

The urban networks of London and New York City are investigated as directed graphs within the paradigm of graph percolation. It has been recently observed that urban networks show a critical percolation transition when a fraction of edges…

Physics and Society · Physics 2020-10-20 Marco Cogoni , Giovanni Busonera

One of the main characteristics of real-world networks is their large clustering. Clustering is one aspect of a more general but much less studied structural organization of networks, i.e. edge multiplicity, defined as the number of…

Physics and Society · Physics 2012-01-31 Vinko Zlatic , Diego Garlaschelli , Guido Caldarelli

In this report we show that in a planar exponentially growing network consisting of $N$ nodes, congestion scales as $O(N^2/\log(N))$ independently of how flows may be routed. This is in contrast to the $O(N^{3/2})$ scaling of congestion in…

Metric Geometry · Mathematics 2012-01-23 Iraj Saniee , Gabriel H. Tucci

Based on a rigorous extension of classical statistical mechanics to networks, we study a specific microscopic network Hamiltonian. The form of this Hamiltonian is derived from the assumption that individual nodes increase/decrease their…

Statistical Mechanics · Physics 2015-06-25 Christoly Biely , Stefan Thurner