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Statistics of delta peaks in the spectral density of large random trees
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We present an analysis of the spectral density of the adjacency matrix of large random trees. We show that there is an infinity of delta peaks at all real numbers which are eigenvalues of finite trees. By exact enumerations and Monte-Carlo simulations, we have numerical estimations of the heights of peaks. In the large tree limit, the sum of their heights is 0.19173 +- 0.00005. Moreover all associated eigenvectors are strictly localized on a finite number of nodes. The rest of the spectral density is a function which vanishes at all positions of peaks, which are a dense subset of real numbers: so this function is almost everywhere discontinuous. Keywords: random tree, spectral density, density of states, adjacency matrix, localization, delta peak.
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Replica theory for the rate functional of the empirical spectral distribution function of diluted Hermitian matrices
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