Sparse regular random graphs: Spectral density and eigenvectors
classification
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math.CO
keywords
eigenvectorsdistributioneigenvaluesempiricalgraphsnumberrandomregular
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We examine the empirical distribution of the eigenvalues and the eigenvectors of adjacency matrices of sparse regular random graphs. We find that when the degree sequence of the graph slowly increases to infinity with the number of vertices, the empirical spectral distribution converges to the semicircle law. Moreover, we prove concentration estimates on the number of eigenvalues over progressively smaller intervals. We also show that, with high probability, all the eigenvectors are delocalized.
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