H.B. Keller Colloquium

Modern socio-technical systems involve a large number of nodes or agents interacting in heterogeneous ways. It is clear that interventions aimed at improving the performance or resilience of these systems should exploit information about the underlying network of interactions, yet most systems of interest are of very large dimension introducing several challenges for the analysis and design of of such large scale networked systems. In this talk, I will illustrate a general methodology to overcome these challenges by i) introducing the concept of a graphon system, which captures the dynamic behavior of an infinite population of agents via the graph limit tool of graphons, and ii) developing a convergence theory of large networked systems to graphon systems. I will illustrate the applicability of this framework by considering two key dynamical processes modeling contagion and synchronization behavior via the linear threshold and Kuramoto model, respectively.