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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.
|Number of pages||17|
|Journal||Physical Review E|
|Publication status||Published - May 2022|
|MoE publication type||A1 Journal article-refereed|
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Source code and for "Directed Percolation in Temporal Networks" and "Directed Percolation in Random Temporal Network Models with Heterogeneities"
Badie Modiri, A. (Creator), Karimi Rizi, A. (Creator), Karsai, M. (Creator) & Kivelä, M. (Creator), 2021
Dataset: Software or code
- 1 Active
Lampinen, J., Roy, C. & Bhattacharya, K.
01/01/2020 → 31/12/2024
Project: EU: Framework programmes funding