论文标题

简单复合物中同步的主稳定性函数

The Master Stability Function for Synchronization in Simplicial Complexes

论文作者

Gambuzza, L. V., Di Patti, F., Gallo, L., Lepri, S., Romance, M., Criado, R., Frasca, M., Latora, V., Boccaletti, S.

论文摘要

复杂系统的所有有趣且引人入胜的集体特性都来自其组件相互作用的复杂方式。物理,生物学,社会科学和工程学领域的各种系统已成功建模为耦合动力学系统的网络,图形链接描述了成对的相互作用。但是,这是一个太大的局限性,因为最近的研究表明,在社会群体,生态系统和人脑中,高阶多体相互作用存在,并且实际上会影响所有这些系统的新兴动态。在这里,我们介绍了一个通用框架,该框架允许研究耦合的动力系统,该系统会以任何可能的顺序计算其相互作用的精确显微镜结构。我们考虑了在简单复合物的节点上组织的相同动力学系统的最一般集合,并通过同步 - 非侵入性耦合函数进行交互。简单复合物可以具有任何维度,这意味着它可以同时解释成对相互作用,三体相互作用等。在如此广泛的背景下,我们表明完全同步是一种不变的解决方案,并且我们为其提供了必要的条件,可以将其视为稳定状态,从主稳定性函数来看。这将现有结果概括为对成对交互(即图形)的有效性,以具有最通用的体系结构的复杂系统。此外,我们展示了如何为特定但经常发生的实例简化该方法,并在合成和现实世界中验证了所有理论预测。鉴于提出的方法的完全一般特征,我们的结果有助于具有多体相互作用的动力学系统理论,并且可以在非常广泛的实际情况下找到应用。

All interesting and fascinating collective properties of a complex system arise from the intricate way in which its components interact. Various systems in physics, biology, social sciences and engineering have been successfully modelled as networks of coupled dynamical systems, where the graph links describe pairwise interactions. This is, however, too strong a limitation, as recent studies have revealed that higher-order many-body interactions are present in social groups, ecosystems and in the human brain, and they actually affect the emergent dynamics of all these systems. Here, we introduce a general framework that allows to study coupled dynamical systems accounting for the precise microscopic structure of their interactions at any possible order. We consider the most general ensemble of identical dynamical systems, organized on the nodes of a simplicial complex, and interacting through synchronization-non-invasive coupling function. The simplicial complex can be of any dimension, meaning that it can account, at the same time, for pairwise interactions, three-body interactions and so on. In such a broad context, we show that complete synchronization exists as an invariant solution, and we give the necessary condition for it to be observed as a stable state in terms of a Master Stability Function. This generalizes the existing results valid for pairwise interactions (i.e. graphs) to the case of complex systems with the most general possible architecture. Moreover, we show how the approach can be simplified for specific, yet frequently occurring, instances, and we verify all our theoretical predictions in synthetic and real-world systems. Given the completely general character of the method proposed, our results contribute to the theory of dynamical systems with many-body interactions and can find applications in an extremely wide range of practical cases.

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