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Scale-free networks in complex systems

机译:复杂系统中的无标度网络

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In the past few years, several studies have explored the topology of interactions in different complex systems. Areas of investigation span from biology to engineering, physics and the social sciences. Although having different microscopic dynamics, the results demonstrate that most systems under consideration tend to self-organize into structures that share common features. In particular, the networks of interaction are characterized by a power law distribution, P(k) ~ k~(-α), in the number of connections per node, k, over several orders of magnitude. Networks that fulfill this propriety of scale-invariance are referred to as "scale-free". In the present work we explore the implication of scale-free topologies in the antiferromagnetic (AF) Ising model and in a stochastic model of opinion formation. In the first case we show that the implicit disorder and frustration lead to a spin-glass phase transition not observed for the AF Ising model on standard lattices. We further illustrate that the opinion formation model produces a coherent, turbulent-like dynamics for a certain range of parameters. The influence, of random or targeted exclusion of nodes is studied.
机译:在过去的几年中,一些研究探索了不同复杂系统中交互的拓扑。研究领域从生物学到工程学,物理学和社会科学。尽管具有不同的微观动力学,但结果表明,所考虑的大多数系统都倾向于自组织成具有共同特征的结构。特别是,交互网络的特征是幂律分布P(k)〜k〜(-α),即每个节点的连接数k超过几个数量级。满足这种规模不变性的网络称为“无规模”。在当前的工作中,我们探讨了无标度拓扑在反铁磁(AF)Ising模型和观点形成的随机模型中的含义。在第一种情况下,我们表明隐式无序和无奈导致标准玻璃上的AF Ising模型未观察到自旋玻璃相变。我们进一步说明,对于一定范围的参数,意见形成模型会产生连贯的,类似湍流的动力学。研究了随机或有目的地排除节点的影响。

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