Cavity approach to the spectral density of sparse symmetric random matrices

Phys Rev E Stat Nonlin Soft Matter Phys. 2008 Sep;78(3 Pt 1):031116. doi: 10.1103/PhysRevE.78.031116. Epub 2008 Sep 10.

Abstract

The spectral density of various ensembles of sparse symmetric random matrices is analyzed using the cavity method. We consider two cases: matrices whose associated graphs are locally treelike, and sparse covariance matrices. We derive a closed set of equations from which the density of eigenvalues can be efficiently calculated. Within this approach, the Wigner semicircle law for Gaussian matrices and the Marcenko-Pastur law for covariance matrices are recovered easily. Our results are compared with numerical diagonalization, showing excellent agreement.