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Power-law statistics and universal scaling in the absence of criticality

机译:幂律统计和普遍扩大在没有关键性的情况下

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摘要

Critical states are sometimes identified experimentally through power-law statistics or universal scaling functions. We show here that such features naturally emerge from networks in self-sustained irregular regimes away from criticality. In these regimes, statistical physics theory of large interacting systems predict a regime where the nodes have independent and identically distributed dynamics. We thus investigated the statistics of a system in which units are replaced by independent stochastic surrogates and found the same power-law statistics, indicating that these are not sufficient to establish criticality.We rather suggest that these are universal features of large-scale networks when considered macroscopically. These results put caution on the interpretation of scaling laws found in nature.
机译:有时通过幂律统计或通用缩放功能通过实验确定关键状态。 我们在这里展示了这些功能自然地从自我持续的不规则制度中的网络远离关键性。 在这些制度中,大型交互系统的统计物理理论预测节点具有独立和相同分布的动态的制度。 因此,我们调查了一个由独立随机代理所取代的系统的统计数据,并发现了相同的幂律统计数据,表明这些不足以建立关键性。我们认为这些是大规模网络的普遍特征 被认为是宏观的。 这些结果谨慎对本质上发现的缩放法律的解释。

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