Fundamental Structural Constraint of Random Scale-Free Networks
classification
❄️ cond-mat.stat-mech
cs.CRphysics.soc-ph
keywords
gammacutoffrandomupperconstraintdegreegraphicalitynetworks
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We study the structural constraint of random scale-free networks that determines possible combinations of the degree exponent $\gamma$ and the upper cutoff $k_c$ in the thermodynamic limit. We employ the framework of graphicality transitions proposed by [Del Genio and co-workers, Phys. Rev. Lett. {\bf 107}, 178701 (2011)], while making it more rigorous and applicable to general values of kc. Using the graphicality criterion, we show that the upper cutoff must be lower than $k_c N^{1/\gamma}$ for $\gamma < 2$, whereas any upper cutoff is allowed for $\gamma > 2$. This result is also numerically verified by both the random and deterministic sampling of degree sequences.
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