报告题目：Beyond networks: introduction to nonlinear dynamics on higher-order structures
报告人：Dr.Riccardo Muolo（Institute of Science Tokyo）
报告时间：2024年11月15日（周五）上午10:00-11:30
主办单位：必威西汉姆官网平台、航空航天结构力学及控制全国重点实验室、国际合作处
报告内容摘要：
Networks are powerful tools in the modeling of complex systems, but they may not capture the right interactions when multiple units are involved simultaneously. Such many-body interactions are encoded by higher-order structures which can be thought as extensions of networks [1]. The most general form is a hypergraph, in which interactions of any order can coexist without any constraint. Over the last years, higher-order structures have been the focus of great excitement, since this novel framework has enormous potential for applications [2]. In this seminar I will introduce higher-order structure and nonlinear dynamics on top of them. I will start by discussing nonlinear dynamical systems on networks and how such a framework can be extended to account for higher-order interactions, to then proceed towards some structural properties of higher-order structures such as hypergraphs and simplicial complexes. In the second part, I will discuss some examples of nonlinear dynamics on hypergraphs, namely, synchronization of phase and chaotic oscillators [3,4], and their extentions in the higher-order framework [5,6]. If time allows, I will also present some recent results from our group.
报告人简介：
Dr. Riccardo Muolo is a Postdoc at Tokyo Institute of Technology (Now with the name Institute of Science Tokyo, due to the merger of two top universities in Japan). He was a Marie Curie PhD student of systems biology at VU Amsterdam from 2018-2019. And he received his PhD degree in applied mathematics from University of Namur in 2023. Since then, he has been a postdoc researcher at the department of systems and control engineering of Tokyo Institute of Technology. His main research interests include nonlinear dynamics on networks and higher-order structures, synchronization, Turing pattern formation, control of dynamical systems and mathematical modeling.
