复杂系统波动标度的Taylor幂律起源
Origins of Taylor's power law for fluctuation scaling in complex systems
摘要：
泰勒涨落标度（FS）在许多自然和人造系统中被观测到，揭示了该定律惊人的普适性。在这里，我们给出强有力的理论基础的起源和丰富的泰勒的FS在不同的复杂系统。我们的方法的普遍性验证对现实世界的数据，从鸟类和昆虫种群，通过人类染色体和交通运输网络的交通强度，股票市场的动态。使用统计物理学的基本原理（平衡和非平衡），我们证明了泰勒定律是由系统的定义良好的态密度（DOS）函数产生的，该函数给出了由相同宏观参数值表征的状态数（即，在给定区域中观察到的鸟的数量、以通过给定观察点的汽车的数量测量的交通强度或以百万美元测量的股票市场中的每日活动）。
英文摘要：
Taylor's fluctuation scaling (FS) has been observed in many natural and man-made systems revealing an amazing universality of the law. Here we give strong theoretical foundations for the origins and abundance of Taylor's FS in different complex systems. The universality of our approach is validated against real world data ranging from bird and insect populations through human chromosomes and traffic intensity in transportation networks to stock market dynamics. Using fundamental principles of statistical physics (both equilibrium and non-equilibrium) we prove that Taylor's law results from the well-defined density of states (DOS) function of a system that gives the number of states characterized by the same value of a macroscopic parameter (i.e., the number of birds observed in a given area, traffic intensity measured as a number of cars passing trough a given observation point or daily activity in the stock market measured in millions of dollars).
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