Prediction of dynamic processes in complex networks

• Grant number: 24/08647-8
• Support Opportunities: Scholarships in Brazil - Doctorate
• Start date: October 01, 2024
• End date: September 30, 2027
• Field of knowledge: Physical Sciences and Mathematics - Physics
• Principal Investigator: Francisco Aparecido Rodrigues
• Grantee: Mariana Macedo dos Santos
• Host Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil

Abstract

The present work aims to investigate how different connection patterns influence dynamic processes in complex networks. Essentially, we will consider methods from statistics and machine learning to predict various variables associated with dynamic processes, such as the level of system synchronization or the fraction of infected vertices in epidemic processes. We will focus on both simple networks and high-order networks, which exhibit non-trivial structures such as simplicial complexes and hyperlinks. Our goal is to develop a general methodology that allows for a better understanding of how connection patterns in the network influence dynamic systems.