Directed Percolation in Temporal Networks

TL;DR

This paper establishes a theoretical framework linking temporal network reachability to directed percolation, revealing phase transitions and critical properties that can be applied to real-world dynamic systems.

Contribution

It formalizes the mapping of temporal network reachability to directed percolation theory, enabling analysis of connectivity phase transitions in temporal networks.

Findings

Reachability in temporal networks exhibits directed percolation phase transition.

Critical percolation properties can be characterized by known directed percolation exponents.

The methodology applies to diverse models and real-world temporal networks.

Abstract

Connectivity and reachability on temporal networks, which can describe the spreading of a disease, decimation of information or the accessibility of a public transport system over time, have been among the main contemporary areas of study in complex systems for the last decade. However, while isotropic percolation theory successfully describes connectivity in static networks, a similar description has not been yet developed for temporal networks. Here address this problem and formalize a mapping of the concept of temporal network reachability to percolation theory. We show that the limited-waiting-time reachability, a generic notion of constrained connectivity in temporal networks, displays directed percolation phase transition in connectivity. Consequently, the critical percolation properties of spreading processes on temporal networks can be estimated by a set of known exponents characterising the directed percolation universality class. This result is robust across a diverse set of temporal network models with different temporal and topological heterogeneities, while by using our methodology we uncover similar reachability phase transitions in real temporal networks too. These findings open up an avenue to apply theory, concepts and methodology from the well-developed directed percolation literature to temporal networks.