Nucleation phenomena and extreme vulnerability of spatial k-core systems

Published: 29 April 2024| Version 1 | DOI: 10.17632/jkvk97nfjc.1
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Description

This dataset contains experimental data related to spatial k-core percolation, a process used to analyze the robustness of spatial k-core systems under random and localized attacks. The dataset includes both network structures and numerical simulation results obtained from experiments conducted on various spatial networks. Network Structures This dataset comprises the link sequences, network structures utilized in numerical simulations of spatial k-core percolation, and edgelist of toy model as a demonstration in the paper. These structures represent networks where nodes correspond to spatial coordinates and edges denote connections between nodes. The link sequences and networks were generated using the zeta model with specific parameters, including a system size of L=1000, characteristic link lengths ranging from zeta = 3 to 1000, and an average degree of k=10. Each file is labeled with a unique identifier (e.g., Link Sequences: "NetID0_avgk10_links_zeta4.pkl", Network Structure: "NetID0_avgk10_zeta3_spatialNet.pkl"). Numerical Simulation Results This dataset includes multiple subdirectories, each representing different experimental configurations and setups. Within each subdirectory, the numerical simulation results are stored in serialized format files. These files are labeled with descriptive names indicating the specific parameters and conditions used in the simulations. Useage: Each file is stored in a serialized format (e.g., Pickle). Some large files are compressed into RAR format; after downloading, these files need to be uncompressed. By loading the serialized files into computational environments (e.g. python or other language), researchers can utilize this network structure dataset to investigate the impact of link length on network resilience under random and localized attacks, and utilize these numerical simulation results to reproduce the figures presented in academic papers or conduct further analyses. For detailed information about the experimental methodology and code implementation, please refer to the associated GitHub code repository (https://github.com/LeyangXue/SpatialKcorePercolation.git) and paper titled “Nucleation phenomena and extreme vulnerability of spatial k-core systems” (https://arxiv.org/abs/2311.13579).

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Institutions

Beijing Normal University - Zhuhai Campus, Bar-Ilan University

Categories

Complex System, Robust Analysis, Spatial Network, Percolation Model

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