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Limit Theorems for Two Classes of Random Matrices with Gaussian Entries

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In this note, we consider ensembles of random symmetric matrices with Gaussian elements. Assume that \( \mathbb{E} \) X ij = 0 and \( \mathbb{E}{X}_{ij}^2={\sigma}_{ij}^2 \) We do not assume that all the σ ij are equal. Assuming that the average of the normalized sums of variances in each row converges to one and the Lindeberg condition holds, we prove that the empirical spectral distribution of eigenvalues converges to Wigner’s semicircle law. We also provide an analogue of this result for sample covariance matrices and prove the convergence to the Marchenko–Pastur law. Bibliography: 5 titles.

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References

  1. Z. D. Bai and J. W. Silverstein, Spectral Analysis of Large Dimensional Random Matrices, 2nd ed., Spinger (2010).

  2. F. Götze, A. A. Naumov, and A. N. Tikhomirov, “Semicircle law for a class of random matrices with dependent entries,” Preprint arXiv.org:0708.2895.

  3. L. A. Pastur, “Spectra of random self-conjugate operators,” Usp. Mat. Nauk, 28, 3–64 (1973).

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  4. S. O’Rourke, “A note on the Marchenko–Pastur law for a class of random matrices with dependent entries,” Preprint arXiv:1201.3554.

  5. E. P. Wigner, “On the distribution of the roots of certain symmetric matrices,” Ann. Math., 67, 325–327 (1958).

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Correspondence to A. A. Naumov.

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Translated from Zapiski Nauchnykh Seminarov POMI, Vol. 412, 2013, pp. 215–226.

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Naumov, A.A. Limit Theorems for Two Classes of Random Matrices with Gaussian Entries. J Math Sci 204, 140–147 (2015). https://doi.org/10.1007/s10958-014-2192-5

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  • DOI: https://doi.org/10.1007/s10958-014-2192-5

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