Numerical Methods for Eigenvalue Distributions of Random Matrices

Abstract

We present efficient numerical techniques for calculation of eigenvalue distributions of random matrices in the beta-ensembles. We compute histograms using direct simulations on very large matrices, by using tridiagonal matrices with appropriate simplifications. The distributions are also obtained by numerical solution of the Painleve II and V equations with high accuracy. For the spacings we show a technique based on the Prolate matrix and Richardson extrapolation, and we compare the distributions with the zeros of the Riemann zeta function.

17 pages, 5 figures

References in corpus (1)

• The Distribution of the Largest Eigenvalue in the Gaussian Ensembles

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