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具有三重相互作用的网络上渗流的动态特性。

The dynamic nature of percolation on networks with triadic interactions.

机构信息

School of Mathematical Sciences, Queen Mary University of London, London, E1 4NS, UK.

Center for Complex Networks and Systems Research, Luddy School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN, 47408, USA.

出版信息

Nat Commun. 2023 Mar 10;14(1):1308. doi: 10.1038/s41467-023-37019-5.

Abstract

Percolation establishes the connectivity of complex networks and is one of the most fundamental critical phenomena for the study of complex systems. On simple networks, percolation displays a second-order phase transition; on multiplex networks, the percolation transition can become discontinuous. However, little is known about percolation in networks with higher-order interactions. Here, we show that percolation can be turned into a fully fledged dynamical process when higher-order interactions are taken into account. By introducing signed triadic interactions, in which a node can regulate the interactions between two other nodes, we define triadic percolation. We uncover that in this paradigmatic model the connectivity of the network changes in time and that the order parameter undergoes a period doubling and a route to chaos. We provide a general theory for triadic percolation which accurately predicts the full phase diagram on random graphs as confirmed by extensive numerical simulations. We find that triadic percolation on real network topologies reveals a similar phenomenology. These results radically change our understanding of percolation and may be used to study complex systems in which the functional connectivity is changing in time dynamically and in a non-trivial way, such as in neural and climate networks.

摘要

渗流建立了复杂网络的连通性,是研究复杂系统的最基本的关键现象之一。在简单网络上,渗流显示出二阶相变;在多重网络上,渗流转变可以变得不连续。然而,对于具有更高阶相互作用的网络中的渗流知之甚少。在这里,我们表明,当考虑到更高阶相互作用时,渗流可以变成一个完全成熟的动力学过程。通过引入带符号的三元相互作用,其中一个节点可以调节两个其他节点之间的相互作用,我们定义了三元渗流。我们发现,在这个典型模型中,网络的连通性随时间变化,序参量经历倍周期和通向混沌的过程。我们提供了三元渗流的一般理论,该理论通过广泛的数值模拟准确地预测了随机图上的全相图。我们发现,在真实网络拓扑上的三元渗流揭示了类似的现象。这些结果从根本上改变了我们对渗流的理解,并且可以用于研究功能连通性随时间动态且以非平凡方式变化的复杂系统,例如在神经和气候网络中。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/82d1/9998640/2027976f9cea/41467_2023_37019_Fig1_HTML.jpg

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