Multiorder Laplacian for synchronization in higher-order networks

M. Lucas, G. Cencetti, F. Battiston
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引用次数: 79

Abstract

Traditionally, interaction systems have been described as networks, where links encode information on the pairwise influences among the nodes. Yet, in many systems, interactions take place in larger groups. Recent work has shown that higher-order interactions between oscillators can significantly affect synchronization. However, these early studies have mostly considered interactions up to 4 oscillators at time, and analytical treatments are limited to the all-to-all setting. Here, we propose a general framework that allows us to effectively study populations of oscillators where higher-order interactions of all possible orders are considered, for any complex topology described by arbitrary hypergraphs, and for general coupling functions. To this scope, we introduce a multi-order Laplacian whose spectrum determines the stability of the synchronized solution. Our framework is validated on three structures of interactions of increasing complexity. First, we study a population with all-to-all interactions at all orders, for which we can derive in a full analytical manner the Lyapunov exponents of the system, and for which we investigate the effect of including attractive and repulsive interactions. Second, we apply the multi-order Laplacian framework to synchronization on a synthetic model with heterogeneous higher-order interactions. Finally, we compare the dynamics of coupled oscillators with higher-order and pairwise couplings only, for a real dataset describing the macaque brain connectome, highlighting the importance of faithfully representing the complexity of interactions in real-world systems. Taken together, our multi-order Laplacian allows us to obtain a complete analytical characterization of the stability of synchrony in arbitrary higher-order networks, paving the way towards a general treatment of dynamical processes beyond pairwise interactions.
高阶网络同步的多阶拉普拉斯算子
传统上,交互系统被描述为网络,其中链路编码节点之间成对影响的信息。然而,在许多系统中,相互作用发生在更大的群体中。最近的研究表明,振子之间的高阶相互作用可以显著影响同步。然而,这些早期研究大多考虑了一次多达4个振荡器的相互作用,并且分析处理仅限于全对全设置。在这里,我们提出了一个通用框架,使我们能够有效地研究振荡种群,其中考虑了所有可能阶的高阶相互作用,对于任意超图描述的任何复杂拓扑,以及一般耦合函数。在这个范围内,我们引入了一个多阶拉普拉斯算子,它的谱决定了同步解的稳定性。我们的框架在三种日益复杂的相互作用结构上得到了验证。首先,我们研究了所有阶的所有对所有相互作用的种群,我们可以用完全解析的方式推导出系统的李雅普诺夫指数,并研究了包括吸引和排斥相互作用的影响。其次,我们将多阶拉普拉斯框架应用于具有异构高阶相互作用的综合模型的同步。最后,对于描述猕猴大脑连接组的真实数据集,我们将耦合振荡器的动力学与高阶和两两耦合进行了比较,强调了忠实地表示现实世界系统中相互作用复杂性的重要性。综上所述,我们的多阶拉普拉斯算子使我们能够获得任意高阶网络中同步稳定性的完整解析表征,为超越两两相互作用的动态过程的一般处理铺平了道路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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