论文标题
多功能拉普拉斯式高阶网络中的同步
Multiorder Laplacian for synchronization in higher-order networks
论文作者
论文摘要
传统上,相互作用系统被描述为网络,其中链接编码了节点之间成对影响的信息。但是,在许多系统中,相互作用发生在较大的组中。最近的工作表明,振荡器之间的高阶相互作用可以显着影响同步。但是,这些早期的研究大多在时间时考虑了高达4个振荡器的相互作用,并且分析治疗仅限于全部环境。在这里,我们提出了一个通用框架,该框架使我们能够有效地研究振荡器的种群,其中考虑了所有可能的订单的高阶相互作用,对于由任意超级学描述的任何复杂拓扑以及用于一般耦合功能的任何复杂拓扑。在此范围内,我们引入了多阶拉普拉斯式的频谱决定同步解决方案的稳定性。我们的框架在复杂性增加的三个相互作用结构上得到了验证。首先,我们在所有顺序研究具有全部相互作用的人群,为此我们可以以完整的分析方式得出该系统的Lyapunov指数,并为此研究包括有吸引力和排斥性相互作用的效果。其次,我们将多阶Laplacian框架应用于与异质高阶相互作用的合成模型同步。最后,我们仅将耦合振荡器的动力学与高阶和成对耦合的动力学进行了比较,这是一个描述猕猴脑连接组的真实数据集,强调了忠实地代表现实世界中相互作用的复杂性的重要性。综上所述,我们的多阶Laplacian使我们能够获得对任意高阶网络中同步稳定性的完整分析表征,从而为超出成对相互作用以外的动态过程的一般处理铺平了道路。
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.