Executive Summary : | The stability of various systems, including epidemic spreading and neuronal signals, has traditionally been based on pair-wise interactions. However, recent research suggests that the stability of large complex systems strongly interconnects between topology and dynamics under pair-wise interactions. The proposal aims to develop a dynamical framework to study complex systems under higher-order interactions, allowing for systematic analysis of the framework to develop a theory for stability analysis. The framework will combine the effects of pair-wise and higher-order interactions with dynamics to predict the dynamic stability of real-world networks. New dynamic metrics derived from topology and dynamics will adapt to changes in the proposed model for complex systems. This project will provide transparent and predictive tools to analyze the stability of real networks, allowing complex dynamical communities to understand the stability of many complex systems more realistically. It will also help in the systematic translation of topological characteristics into dynamical behavior. |