Asymptotic behavior for log-determinants of several non-Hermitian random matrices

Lei CHEN , Shaochen WANG

Front. Math. China ›› 2017, Vol. 12 ›› Issue (4) : 805 -819.

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Front. Math. China ›› 2017, Vol. 12 ›› Issue (4) : 805 -819. DOI: 10.1007/s11464-017-0629-0
RESEARCH ARTICLE
RESEARCH ARTICLE

Asymptotic behavior for log-determinants of several non-Hermitian random matrices

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Abstract

We study the asymptotic behavior for log-determinants of two unitary but non-Hermitian random matrices: the spherical ensembles A−1B, where A and B are independent complex Ginibre ensembles and the truncation of circular unitary ensembles. The corresponding Berry-Esseen bounds and Cramér type moderate deviations are established. Our method is based on the estimates of corresponding cumulants. Numerical simulations are also presented to illustrate the theoretical results.

Keywords

Log-determinants / Berry-Esseen bounds / moderate deviations / spherical ensembles / circular unitary ensembles

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Lei CHEN, Shaochen WANG. Asymptotic behavior for log-determinants of several non-Hermitian random matrices. Front. Math. China, 2017, 12(4): 805-819 DOI:10.1007/s11464-017-0629-0

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References

[1]

AkemannG, BurdaZ. Universal microscopic correlation functions for products of independent Ginibre matrices. J Phys A, 2012, 45(46): 465201

[2]

BaoZ G, PanG M, ZhouW. The logarithmic law of random determinant. Bernoulli, 2015, 21(3): 1600–1628

[3]

CaiT, LiangT Y, ZhouH. Law of log determinant of sample covariance matrix and optimal estimation of differential entropy for high-dimensional Gaussian distributions. J Multivariate Anal, 2015, 137: 161–172

[4]

ChenL, GaoF Q, WangS C. Berry-esseen bounds and Cramér type large deviations for eigenvalues of random matrices. Sci China Ser A, 2015, 58(9): 1959–1980

[5]

DelannayR, Le CaërG. Distribution of the determinant of a random real-symmetric matrix from the Gaussian orthogonal ensemble. Phys Rev E, 2000, 62(2): 1526

[6]

DöringH, EichelsbacherP. Moderate deviations for the determinant of Wigner matrices. In: Limit Theorems in Probability, Statistics and Number Theory. Berlin: Springer, 2013, 253–275

[7]

ForresterP J, MaysA. Pfaffian point process for the Gaussian real generalized eigenvalue problem. Probab Theory Related Fields, 2012, 154(1-2): 1–47

[8]

GirkoV L. The central limit theorem for random determinants. Theory Probab Appl, 1980, 24(4): 729–740

[9]

GoodmanN R. The distribution of the determinant of a complex Wishart distributed matrix. Ann Math statist, 1963, 34(1): 178–180

[10]

JiangH, WangS C. Cramér type moderate deviation and Berry-Esseen bound for the Log-determinant of sample covariance matrix. Preprint

[11]

JiangT F, QiY C. Spectral radii of large non-hermitian random matrices. J Theoret Probab, 2015, 1–39

[12]

KrishnapurM. From random matrices to random analytic functions. Ann Probab, 2009, 37(1): 314–346

[13]

LebedevN N. Special Functions and their Applications. Englewood Cliffs: Prentice-Hall Inc, 1965

[14]

MezzadriF. How to generate random matrices from the classical compact groups. Notices Amer Math Soc, 2007, 54(5): 592–604

[15]

NguyenH, VuV. Random matrices: Law of the determinant. Ann Probab, 2014, 42(1): 146–167

[16]

SaulisL, StatuleviciusV A. Limit Theorems for Large Deviations. New York: Springer, 1991

[17]

TaoT, VuV. A central limit theorem for the determinant of a Wigner matrix. Adv Math, 2012, 231(1): 74–101

[18]

ZyczkowskiK. Truncations of random unitary matrices. J Phys A, 2000, 33(10): 2045

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