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Resilience of networks with community structure behaves as if under an external field

机译:具有社区结构的网络的弹性就像在外部环境下一样

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摘要

Although detecting and characterizing community structure is key in the study of networked systems, we still do not understand how community structure affects systemic resilience and stability. We use percolation theory to develop a framework for studying the resilience of networks with a community structure. We find both analytically and numerically that interlinks (the connections among communities) affect the percolation phase transition in a way similar to an external field in a ferromagnetic– paramagnetic spin system. We also study universality class by defining the analogous critical exponents δ and γ, and we find that their values in various models and in real-world coauthor networks follow the fundamental scaling relations found in physical phase transitions. The methodology and results presented here facilitate the study of network resilience and also provide a way to understand phase transitions under external fields.
机译:尽管检测和表征社区结构是研究网络系统的关键,但是我们仍然不了解社区结构如何影响系统的弹性和稳定性。我们使用渗流理论来开发一个框架,以研究具有社区结构的网络的弹性。我们在分析和数值上都发现,互连(社区之间的联系)以类似于铁磁-顺磁自旋系统中的外场的方式影响渗流相变。我们还通过定义相似的临界指数δ和γ来研究通用性类别,我们发现它们在各种模型和现实世界中的合著者网络中的值遵循在物理相变中发现的基本比例关系。此处介绍的方法和结果有助于研究网络弹性,也提供了一种了解外部领域下相变的方法。

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