Titlebook: Statistical Mechanics of Complex Networks; Romualdo Pastor-Satorras,Miguel Rubi,Albert Diaz-G Book 2003 Springer-Verlag Berlin Heidelberg

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Food Web Structure and the Evolution of Complex Networks,stability against species removal. We present the analysis of the data for both real food webs and numerical simulations of a growing network model. Our results allow us to conclude that real food webs display a high degree of both efficiency and stability due to the evolving character of their topology.

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Introduction, that interact mainly via non-local interactions. In this sense, while the study of their homogeneous counterparts with local interactions has resulted in most significative achievements (consider for example the theory of critical phenomena), heterogeneous systems have usually been the subject of m

Curmudgeon

Rate Equation Approach for Growing Networks,nodes are introduced sequentially and attach to an earlier node of degree . with rate ..˜.. is computed. Very different behaviors arise for γ < 1, γ = 1 and γ > 1. The rate equation approach is extended to determine the joint order-degree distribution, the degree correlations of neighboring nodes, a

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Directed and Non-directed Scale-Free Networks,(.)=... We review results for the properties of such networks, emphasizing the structural properties of these networks. We begin with normal random scale-free networks and present their percolation properties. We also review results for directed scale-free networks and their percolation properties.

Barter

Hierarchical Organization of Modularity in Complex Networks,the scale-free nature and high clustering of real networks are the consequence of a hierarchical organization, implying that small groups of nodes form increasingly large groups in a hierarchical manner, while maintaining a scale-free topology. In hierarchical networks the clustering coefficient fol

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Mixing Patterns and Community Structure in Networks,hin groups than between them. Here we describe a new computer algorithm that detects structure of this kind. We apply the algorithm to a number of real-world networks and show that they do indeed possess non-trivial community structure. We suggest a possible explanation for this structure in the mec

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毛细血管

Optimization in Complex Networks,icial nets display a surprisingly widespread feature: the presence of highly heterogeneous distributions of links, providing an extraordinary source of robustness against perturbations. Although most theories concerning the origin of these topologies use growing graphs, here we show that a simple op

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