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Percolation in Self-Similar Networks
Open accessAbstract
We provide a simple proof that graphs in a general class of self-similar networks have zero percolation threshold. The considered self-similar networks include random scale-free graphs with given expected node degrees and zero clustering, scale-free graphs with finite clustering and metric structure, growing scale-free networks, and many real networks. The proof and the derivation of the giant component size do not require the assumption that networks are treelike. Our results rely only on the observation that self-similar networks possess a hierarchy of nested subgraphs whose average degree grows with their depth in the hierarchy. We conjecture that this property is pivotal for percolation in networks.
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The proposed gravity model is based on the connectivity law proposed for complex networks with underlying metric spaces.
“Our gravity model is based on the connectivity law proposed for complex networks with underlying metric spaces [16, 17]”
From The hidden hyperbolic geometry of international trade: World Trade Atlas 1870-2013 (2015) · cites this paper as [17]
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The hidden hyperbolic geometry of international trade: World Trade Atlas 1870-2013
García-Pérez, G., Boguñá, M., Allard, A., & Serrano, M. Á. (2015) · arXiv · doi:10.48550/arxiv.1512.02233 · Cited by 10
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Metadata
- Authors
- Serrano, M. Á., Krioukov, D., & Boguñá, M.
- Affiliations
- Universitat de Barcelona (ES)
- University of California San Diego (US)
- Venue
- Physical Review Letters
- Publisher
- American Physical Society (APS)
- Published
- 2011-01-25
- Volume
- 106
- Issue
- 4
- Pages
- 048701-048701
- ISSN
- 0031-9007 (ISSN-L)
- 1079-7114
- OpenAlex
- W2066877881
- Cited by
- 47
- References
- 0
- Citations by year
- 2026: 3 · 2025: 4 · 2024: 3 · 2023: 3 · 2022: 2 · 2021: 6 · 2019: 1 · 2018: 3 · 2017: 2 · 2016: 5 · 2015: 6 · 2014: 5 · 2013: 1 · 2012: 2
- FWCI
- 2.20
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Physical Review Letters (publishedVersion)
- PubMed (publishedVersion)
- RECERCAT (Consorci de Serveis Universitaris de Catalunya) (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- Dipòsit Digital de la Universitat de Barcelona (Universitat de Barcelona) (submittedVersion, public-domain)
- arXiv (Cornell University)
- Funders
- National Science Foundation
- Topics
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
- Physical Sciences › Physics and Astronomy › Condensed Matter Physics › Theoretical and Computational Physics
- Physical Sciences › Mathematics › Mathematical Physics › Stochastic processes and statistical mechanics
- Keywords
- percolation threshold, self-similar networks, scale-free networks, network hierarchy, growing networks, clustering, real-world networks
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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