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Sparse random matrices: the eigenvalue spectrum revisited

Guilhem Semerjian1 and Leticia F Cugliandolo1,2

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We revisit the derivation of the density of states of sparse random matrices. We derive a recursion relation that allows one to compute the spectrum of the matrix of incidence for finite trees that determines completely the low concentration limit. Using the iterative scheme introduced by Biroli and Monasson (1999 J. Phys. A: Math. Gen. 32 L255) we find an approximate expression for the density of states expected to hold exactly in the opposite limit of large but finite concentration. The combination of the two methods yields a very simple geometric interpretation of the tails of the spectrum. We test the analytic results with numerical simulations and we suggest an indirect numerical method to explore the tails of the spectrum.


PACS

02.10.Yn Matrix theory

02.60.-x Numerical approximation and analysis

75.50.Lk Spin glasses and other random magnets

MSC

03D80 Applications of computability and recursion theory

15A52 Random matrices

65F10 Iterative methods for linear systems (See also 65N22)

Subjects

Mathematical physics

Computational physics

Condensed matter: electrical, magnetic and optical

Dates

Issue 23 (14 June 2002)

Received 27 February 2002, in final form 19 April 2002

Published 31 May 2002



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