Spectral convergence of random regular graphs: Chebyshev polynomials, non-backtracking walks, and unitary-color extensions

Abstract

In this paper, we give a short proof of the weak convergence to the Kesten-McKay distribution for the normalized spectral measures of random N-lifts. This result is derived by generalizing a formula of Friedman involving Chebyshev polynomials and non-backtracking walks. We also extend a criterion of Sodin on the convergence of graph spectral measures to regular graphs of growing degree. As a result, we show that for a sequence of random (qn+1)-regular graphs Gn with n vertices, if qn = no(1) and qn tends to infinity, the normalized spectral measure converges almost surely in p-Wasserstein distance to the semicircle distribution for any p ∈ [1, ∞). This strengthens a result of Dumitriu and Pal. Many of the results are extended to unitary-colored regular graphs.

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