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Directed percolation in random temporal network models with heterogeneities
Title / Series / Name
Publication Volume
Publication Issue
Pages
Editors
Keywords
Statistical and Nonlinear Physics
Statistics and Probability
Condensed Matter Physics
Statistics and Probability
Condensed Matter Physics
URI
https://hdl.handle.net/20.500.14018/26518
Abstract
The event graph representation of temporal networks suggests that the connectivity of temporal structures can be mapped to a directed percolation problem. However, similarly to percolation theory on static networks, this mapping is valid under the approximation that the structure and interaction dynamics of the temporal network are determined by its local properties, and, otherwise, it is maximally random. We challenge these conditions and demonstrate the robustness of this mapping in case of more complicated systems. We systematically analyze random and regular network topologies and heterogeneous link-activation processes driven by bursty renewal or self-exciting processes using numerical simulation and finite-size scaling methods. We find that the critical percolation exponents characterizing the temporal network are not sensitive to many structural and dynamical network heterogeneities, while they recover known scaling exponents characterizing directed percolation on low-dimensional lattices. While it is not possible to demonstrate the validity of this mapping for all temporal network models, our results establish the first batch of evidence supporting the robustness of the scaling relationships in the limited-time reachability of temporal networks.
Topic
Publisher
Place of Publication
Type
Journal article
Date
2022-05
Language
ISBN
Identifiers
10.1103/PhysRevE.105.054313