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Highly nonlinear complexity of interaction dynamics in scale-free networks

机译:无标度网络中交互动力学的高度非线性复杂性

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摘要

Interaction dynamics induced by finite-capacity effect is a typical diffusion model on networks. Although several significant properties of it like condensation have been well studied, the origin of its highly nonlinear complexity, influenced by complex structure and interactive behavior, is still missing. Aimed at filling this gap, we propose entropy to quantify the complexity and exhibit its strong dependence on two coupled crucial elements of nodes, the local topology and the finite capacity. Further, the performance of interaction dynamics, efficiency function is also analyzed in terms of entropy rate and relatively promoted through routing strategy arguments supported by maximum entropy theory studies. This will play a crucial role for inference problems emerging in the field of interaction dynamics on complex networks.
机译:有限容量效应引起的相互作用动力学是网络上的典型扩散模型。尽管已经对其缩合的几个重要特性进行了很好的研究,但仍缺乏其高度非线性复杂性(受复杂结构和交互行为影响)的起源。为了填补这一空白,我们提出了熵来量化复杂性,并表现出它对节点的两个耦合关键元素,局部拓扑和有限容量的强烈依赖。此外,还根据熵率分析了交互动力学,效率函数的性能,并通过最大熵理论研究支持的路由策略论证相对促进了交互动力学,效率函数的性能。这对于复杂网络上的交互动力学领域中出现的推理问题将发挥至关重要的作用。

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