Mapping temporal-network percolation to weighted, static event graphs

Mapping temporal-network percolation to weighted, static event graphs

Blog Article

Abstract The dynamics of diffusion-like processes on temporal networks are influenced by correlations in the times of contacts.This influence is particularly strong for processes where the spreading agent has a limited lifetime at nodes: disease spreading (recovery time), diffusion of rumors (lifetime of information), and passenger routing (maximum acceptable time between transfers).We introduce lycogel weighted event graphs as a powerful and fast framework for studying connectivity determined by time-respecting paths where the allowed waiting times between contacts have an upper limit.We study percolation on the weighted event graphs and in the underlying temporal networks, with simulated and real-world networks.We show that this type of temporal-network percolation is analogous to directed percolation, and that g35 coupe fender it can be characterized by multiple order parameters.