Nurisso Marco, Arnaudon Alexis, Lucas Maxime, Peach Robert L, Expert Paul, Vaccarino Francesco, Petri Giovanni
CENTAI Institute, Turin 10138, Italy.
Dipartimento di Scienze Matematiche, Politecnico di Torino, Turin 10129, Italy.
Chaos. 2024 May 1;34(5). doi: 10.1063/5.0169388.
Simplicial Kuramoto models have emerged as a diverse and intriguing class of models describing oscillators on simplices rather than nodes. In this paper, we present a unified framework to describe different variants of these models, categorized into three main groups: "simple" models, "Hodge-coupled" models, and "order-coupled" (Dirac) models. Our framework is based on topology and discrete differential geometry, as well as gradient systems and frustrations, and permits a systematic analysis of their properties. We establish an equivalence between the simple simplicial Kuramoto model and the standard Kuramoto model on pairwise networks under the condition of manifoldness of the simplicial complex. Then, starting from simple models, we describe the notion of simplicial synchronization and derive bounds on the coupling strength necessary or sufficient for achieving it. For some variants, we generalize these results and provide new ones, such as the controllability of equilibrium solutions. Finally, we explore a potential application in the reconstruction of brain functional connectivity from structural connectomes and find that simple edge-based Kuramoto models perform competitively or even outperform complex extensions of node-based models.
单纯形Kuramoto模型已成为一类多样且引人入胜的模型,用于描述单纯形而非节点上的振子。在本文中,我们提出了一个统一框架来描述这些模型的不同变体,分为三大类:“简单”模型、“霍奇耦合”模型和“序耦合”(狄拉克)模型。我们的框架基于拓扑学和离散微分几何,以及梯度系统和挫折感,并允许对其性质进行系统分析。在单纯复形具有流形性的条件下,我们建立了简单单纯形Kuramoto模型与成对网络上的标准Kuramoto模型之间的等价关系。然后,从简单模型出发,我们描述了单纯形同步的概念,并推导了实现它所需或充分的耦合强度的界限。对于一些变体,我们推广了这些结果并提供了新的结果,例如平衡解的可控性。最后,我们探索了从结构连接组重建脑功能连接的潜在应用,发现基于简单边的Kuramoto模型具有竞争力,甚至优于基于节点的模型的复杂扩展。