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Albert-László Barabási【复杂网络大牛,现哈佛任职】
doi:10.1038/nphys2188
Reductionism, as a paradigm, is expired, and complexity, as a field, is tired. Data-based mathematical models of complex systems are offering a fresh perspective, rapidly developing into a new discipline: network science.
James Crutchfield
doi:10.1038/nphys2190
A completely ordered universe is as unexciting as an entirely disordered one. Interesting 'complex' phenomena arise in a middle ground. This article reviews the tools that have been developed to quantify structural complexity and to automatically discover patterns hidden between order and chaos.
Abstract- Between order and chaos | Full text- Between order and chaos | PDF (1,545KB)- Between order and chaos
M. E. J. Newman
doi:10.1038/nphys2162
Networks have proved to be useful representations of complex systems. Within these networks, there are typically a number of subsystems defined by only a subset of nodes and edges. Detecting these structures often provides important information about the organization and functioning of the overall network. Here, progress towards quantifying medium- and large-scale structures within complex networks is reviewed.
Abstract- Communities, modules and large-scale structure in networks | Full text-Communities, modules and large-scale structure in networks | PDF (1,545KB)- Communities, modules and large-scale structure in networks
Alessandro Vespignani
doi:10.1038/nphys2160
Vast amounts of data are available about complex technological systems and how we use them. These data provide the basis not only for mapping out connectivity patterns, but also for the study of dynamical phenomena, including epidemic outbreaks and routing of information through computer networks. This article reviews the fundamental tools for modelling such dynamical processes and discusses a number of applications.
Abstract-Modelling dynamical processes in complex socio-technical systems | Full text- Modelling dynamical processes in complex socio-technical systems | PDF (1,545KB)-
Jianxi Gao, Sergey V. Buldyrev, H. Eugene Stanley and Shlomo Havlin
doi:10.1038/nphys2180
Aspects concerning the structure and behaviours of individual networks have been studied intensely in the past decade, but the exploration of interdependent systems in the context of complex networks has started only recently. This article reviews a general framework for modelling the percolation properties of interacting networks and the first results drawn from its study.
Abstract-Networks formed from interdependent networks | Full text- Networks formed from interdependent networks | PDF (265KB)
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