arXiv:1112.0752 [math.PR]AbstractReferencesReviewsResources
Random matrices: Law of the determinant
Published 2011-12-04, updated 2014-01-13Version 3
Let $A_n$ be an $n$ by $n$ random matrix whose entries are independent real random variables with mean zero, variance one and with subexponential tail. We show that the logarithm of $|\det A_n|$ satisfies a central limit theorem. More precisely, \begin{eqnarray*}\sup_{x\in {\mathbf {R}}}\biggl|{\mathbf {P}}\biggl(\frac{\log(|\det A_n|)-({1}/{2})\log (n-1)!}{\sqrt{({1}/{2})\log n}}\le x\biggr)-{\mathbf {P}}\bigl(\mathbf {N}(0,1)\le x\bigr)\biggr|\\\qquad\le\log^{-{1}/{3}+o(1)}n.\end{eqnarray*}
Comments: Published in at http://dx.doi.org/10.1214/12-AOP791 the Annals of Probability (http://www.imstat.org/aop/) by the Institute of Mathematical Statistics (http://www.imstat.org)
Journal: Annals of Probability 2014, Vol. 42, No. 1, 146-167
DOI: 10.1214/12-AOP791
Categories: math.PR
Keywords: random matrices, determinant, independent real random variables, central limit theorem, random matrix
Tags: journal article
Related articles: Most relevant | Search more
Optimal On-Line Selection of an Alternating Subsequence: A Central Limit Theorem
arXiv:math/0702358 [math.PR] (Published 2007-02-13)
Law of Large Numbers and Central Limit Theorem under Nonlinear Expectations
Central Limit Theorem for a Class of Relativistic Diffusions