Spectral distributions of adjacency and Laplacian matrices of random graphs

Details Spectral distributions of adjacency and Laplacian matrices of random graphs Spectral distributions of adjacency and Laplacian matrices of random graphs

2010-11-11

arxiv.org/abs/1011.2608v1

Annals of Applied Probability 2010, Vol. 20, No. 6, 2086-2117

Mathematics

Probability

Published in at http://dx.doi.org/10.1214/10-AAP677 the Annals of Applied Probability (http://www.imstat.org/aap/) by the Inst

Scientific paper

10.1214/10-AAP677

In this paper, we investigate the spectral properties of the adjacency and the Laplacian matrices of random graphs. We prove that: (i) the law of large numbers for the spectral norms and the largest eigenvalues of the adjacency and the Laplacian matrices; (ii) under some further independent conditions, the normalized largest eigenvalues of the Laplacian matrices are dense in a compact interval almost surely; (iii) the empirical distributions of the eigenvalues of the Laplacian matrices converge weakly to the free convolution of the standard Gaussian distribution and the Wigner's semi-circular law; (iv) the empirical distributions of the eigenvalues of the adjacency matrices converge weakly to the Wigner's semi-circular law.

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