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Recursion for the Smallest Eigenvalue Density of β -Wishart–Laguerre Ensemble
Published in Springer New York LLC
2019
Volume: 175
   
Issue: 1
Pages: 126 - 149
Abstract
The statistics of the smallest eigenvalue of Wishart–Laguerre ensemble is important from several perspectives. The smallest eigenvalue density is typically expressible in terms of determinants or Pfaffians. These results are of utmost significance in understanding the spectral behavior of Wishart–Laguerre ensembles and, among other things, unveil the underlying universality aspects in the asymptotic limits. However, obtaining exact and explicit expressions by expanding determinants or Pfaffians becomes impractical if large dimension matrices are involved. For the real matrices (β= 1) Edelman has provided an efficient recurrence scheme to work out exact and explicit results for the smallest eigenvalue density which does not involve determinants or matrices. Very recently, an analogous recurrence scheme has been obtained for the complex matrices (β= 2). In the present work we extend this to β-Wishart–Laguerre ensembles for the case when exponent α in the associated Laguerre weight function, λ α e - β λ / 2 , is a non-negative integer, while β is positive real. This also gives access to the smallest eigenvalue density of fixed trace β-Wishart–Laguerre ensemble, as well as moments for both cases. Moreover, comparison with earlier results for the smallest eigenvalue density in terms of certain hypergeometric function of matrix argument results in an effective way of evaluating these explicitly. Exact evaluations for large values of n (the matrix dimension) and α also enable us to compare with Tracy–Widom density and large deviation results of Katzav and Castillo. We also use our result to obtain the density of the largest of the proper delay times which are eigenvalues of the Wigner–Smith matrix and are relevant to the problem of quantum chaotic scattering. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.
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Published in Springer New York LLC
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