{
  "id": "cond-mat/0603353",
  "version": "v2",
  "published": "2006-03-13T14:24:15.000Z",
  "updated": "2006-08-18T20:39:05.000Z",
  "title": "Percolation and Epidemic Thresholds in Clustered Networks",
  "authors": [
    "M. Angeles Serrano",
    "Marian Boguna"
  ],
  "comment": "4 Pages and 3 Figures. Final version to appear in PRL",
  "journal": "Physical Review Letters 97, 088701 (2006)",
  "doi": "10.1103/PhysRevLett.97.088701",
  "categories": [
    "cond-mat.dis-nn"
  ],
  "abstract": "We develop a theoretical approach to percolation in random clustered networks. We find that, although clustering in scale-free networks can strongly affect some percolation properties, such as the size and the resilience of the giant connected component, it cannot restore a finite percolation threshold. In turn, this implies the absence of an epidemic threshold in this class of networks extending, thus, this result to a wide variety of real scale-free networks which shows a high level of transitivity. Our findings are in good agreement with numerical simulations.",
  "revisions": [
    {
      "version": "v2",
      "updated": "2006-08-18T20:39:05.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "epidemic threshold",
      "real scale-free networks",
      "finite percolation threshold",
      "percolation properties",
      "giant connected component"
    ],
    "tags": [
      "journal article"
    ],
    "publication": {
      "publisher": "APS",
      "journal": "Phys. Rev. Lett."
    },
    "note": {
      "typesetting": "TeX",
      "pages": 4,
      "language": "en",
      "license": "arXiv",
      "status": "editable"
    }
  }
}