Susceptibility in subcritical random graphs
classification
🧮 math.PR
math.CO
keywords
randomsusceptibilityprovesubcriticalaroundasymptoticallyasymptoticscomponent
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We study the evolution of the susceptibility in the subcritical random graph $G(n,p)$ as $n$ tends to infinity. We obtain precise asymptotics of its expectation and variance, and show it obeys a law of large numbers. We also prove that the scaled fluctuations of the susceptibility around its deterministic limit converge to a Gaussian law. We further extend our results to higher moments of the component size of a random vertex, and prove that they are jointly asymptotically normal.
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