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Title:
Statistical mechanics of complex networks
Authors:
Albert, Réka; Barabási, Albert-László
Affiliation:
AA(Department of Physics, University of Notre Dame, Notre Dame, Indiana 46556), AB(Department of Physics, University of Notre Dame, Notre Dame, Indiana 46556)
Publication:
Reviews of Modern Physics, vol. 74, Issue 1, pp. 47-97 (RvMP Homepage)
Publication Date:
01/2002
Origin:
APS
PACS Keywords:
Classical statistical mechanics, World Wide Web Internet, Fluctuation phenomena random processes noise and Brownian motion, Book reviews, Logic set theory and algebra, General topology, Probability theory stochastic processes and statistics, Computational modeling, simulation
DOI:
10.1103/RevModPhys.74.47
Bibliographic Code:
2002RvMP...74...47A

Abstract

Complex networks describe a wide range of systems in nature and society. Frequently cited examples include the cell, a network of chemicals linked by chemical reactions, and the Internet, a network of routers and computers connected by physical links. While traditionally these systems have been modeled as random graphs, it is increasingly recognized that the topology and evolution of real networks are governed by robust organizing principles. This article reviews the recent advances in the field of complex networks, focusing on the statistical mechanics of network topology and dynamics. After reviewing the empirical data that motivated the recent interest in networks, the authors discuss the main models and analytical tools, covering random graphs, small-world and scale-free networks, the emerging theory of evolving networks, and the interplay between topology and the network's robustness against failures and attacks.
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