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. 2020 Oct 27;10:18387. doi: 10.1038/s41598-020-75147-w

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© The Author(s) 2020

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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Graph representation of the US power grid (top left panel) and realizations of sub-sampled networks with $N^{'} = 740$ and $⟨ k ⟩ = 0.4$ (top right), $N^{'} = 1851$ and $⟨ k ⟩ = 1.01$ (bottom left), $N^{'} = 3492$ and $⟨ k ⟩ = 1.89$ (bottom right); the largest connected component in each sub-sampled network is highlighted in red (the layout of the graph is different from that used in Fig. 4). Graphs are generated with the Python libraries Graphviz 2.38³⁷ and NetworkX 2.4³⁸.