Anatomy of a young giant component in the random graph

  • Authors:
  • Jian Ding;Jeong Han Kim;Eyal Lubetzky;Yuval Peres

  • Affiliations:
  • Department of Statistics, UC Berkeley, Berkeley, California 94720;Department of Mathematics, Yonsei University, Seoul 120-749, Korea and National Institute for Mathematical Sciences, Daejeon 305-340, Korea;Microsoft Research, One Microsoft Way Redmond, Washington 98052-6399;Microsoft Research, One Microsoft Way Redmond, Washington 98052-6399

  • Venue:
  • Random Structures & Algorithms
  • Year:
  • 2011

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Abstract

We provide a complete description of the giant component of the Erdős-Rényi random graph \documentclass{article} \usepackage{mathrsfs} \usepackage{amsmath} \pagestyle{empty} \begin{document} \begin{align*}{\mathcal{G}}(n,p)\end{align*} \end{document} **image** as soon as it emerges from the scaling window, i.e., for p = (1+ε)/n where ε3n →∞ and ε = o(1). Our description is particularly simple for ε = o(n-1/4), where the giant component \documentclass{article} \usepackage{mathrsfs} \usepackage{amsmath} \pagestyle{empty} \begin{document} \begin{align*}{\mathcal{C}_1}\end{align*} \end{document} **image** is contiguous with the following model (i.e., every graph property that holds with high probability for this model also holds w.h.p. for \documentclass{article} \usepackage{mathrsfs} \usepackage{amsmath} \pagestyle{empty} \begin{document} \begin{align*}{\mathcal{C}_1}\end{align*} \end{document} **image** ). Let Z be normal with mean \documentclass{article} \usepackage{mathrsfs} \usepackage{amsmath} \pagestyle{empty} \begin{document} \begin{align*}\frac{2}{3} \varepsilon^3 n\end{align*} \end{document} **image** and variance ε3n, and let \documentclass{article} \usepackage{mathrsfs} \usepackage{amsmath} \pagestyle{empty} \begin{document} \begin{align*}\mathcal{K}\end{align*} \end{document} **image** be a random 3-regular graph on \documentclass{article} \usepackage{mathrsfs} \usepackage{amsmath} \pagestyle{empty} \begin{document} \begin{align*}2\left\lfloor Z\right\rfloor\end{align*} \end{document} **image** vertices. Replace each edge of \documentclass{article} \usepackage{mathrsfs} \usepackage{amsmath} \pagestyle{empty} \begin{document} \begin{align*}\mathcal{K}\end{align*} \end{document} **image** by a path, where the path lengths are i.i.d. geometric with mean 1/ε. Finally, attach an independent Poisson( 1-ε )-Galton-Watson tree to each vertex. A similar picture is obtained for larger ε = o(1), in which case the random 3-regular graph is replaced by a random graph with Nk vertices of degree k for k ≥ 3, where Nk has mean and variance of order εkn. This description enables us to determine fundamental characteristics of the supercritical random graph. Namely, we can infer the asymptotics of the diameter of the giant component for any rate of decay of ε, as well as the mixing time of the random walk on \documentclass{article} \usepackage{mathrsfs} \usepackage{amsmath} \pagestyle{empty} \begin{document} \begin{align*}{\mathcal{C}_1}\end{align*} \end{document} **image** . © 2010 Wiley Periodicals, Inc. Random Struct. Alg., 39, 139–178, 2011 © 2011 Wiley Periodicals, Inc.