Abstract: What if you had a collection of identical systems each, interacting with one another, and you could make all of them behave in the same manner simply by adjusting the strengths of their interactions? The classical answer involves identifying how the systems are connected (a digraph), modeling each system’s individual behaviour (a differential equation), computing the digraph Laplacian, and then solving matrix inequalities for the coupling strengths. Manageable for small networks but for large ones, this pipeline regularly runs into infeasibility, and detailed system models are often simply unavailable.

What if we could bypass all of this? Instead of solving matrix inequalities, we just look at the digraph, trace some paths, and directly compute which interactions need to be strengthened and which scaled back and the systems fall into sync. No inequality solvers. No detailed models. Just graph theory, a mild assumption on how wild the dynamics can get, and a clean algorithm that tells you exactly what to do.

This talk presents precisely such a method. We show that synchronization in a large class of nonlinear dynamical networks can be achieved by working directly with the connectivity digraph computing coupling strengths from connectivity alone.

Event Details
Title: Synchronization of Nonlinear Dynamical Networks: A (purely) Graph-Theoretic Perspective
Date: April 17, 2026 at 04:00 PM
Venue: ESB 234 (Malaviya Hall)
Speaker: Mr. Aandrew Baggio S (EE20D067)
Guide: Dr. Rachel Kalpana Kalaimani
Type: PHD seminar

Updated: