Cavity approach to the spectral density of sparse symmetric random matrices

Tim Rogers, Isaac Pérez Castillo, Reimer Kühn, and Koujin Takeda
Phys. Rev. E 78, 031116 – Published 10 September 2008

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 Marčenko-Pastur law for covariance matrices are recovered easily. Our results are compared with numerical diagonalization, showing excellent agreement.

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  • Received 13 March 2008

DOI:https://doi.org/10.1103/PhysRevE.78.031116

©2008 American Physical Society

Authors & Affiliations

Tim Rogers, Isaac Pérez Castillo, and Reimer Kühn

  • Department of Mathematics, King’s College London, Strand, London WC2R 2LS, United Kingdom

Koujin Takeda

  • Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, Yokohama 226-8502, Japan and Department of Mathematics, King’s College London, Strand, London WC2R 2LS, United Kingdom

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Issue

Vol. 78, Iss. 3 — September 2008

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