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arxiv: 1106.5150 · v2 · pith:VXI7ATGMnew · submitted 2011-06-25 · ⚛️ physics.soc-ph · cond-mat.stat-mech· cs.SI

All scale-free networks are sparse

classification ⚛️ physics.soc-ph cond-mat.stat-mechcs.SI
keywords degreegivennetworksscale-freesparseanalyticalappliedarguments
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We study the realizability of scale free-networks with a given degree sequence, showing that the fraction of realizable sequences undergoes two first-order transitions at the values 0 and 2 of the power-law exponent. We substantiate this finding by analytical reasoning and by a numerical method, proposed here, based on extreme value arguments, which can be applied to any given degree distribution. Our results reveal a fundamental reason why large scale-free networks without constraints on minimum and maximum degree must be sparse.

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