Mathematics – Probability
Scientific paper
2010-10-02
Mathematics
Probability
25 pages, no figures. This is a final version of a paper that was previously titled "Large deviations from freeness". Accepted
Scientific paper
Let H=A+UBU* where A and B are two N-by-N Hermitian matrices and U is a Haar-distributed random unitary matrix, and let \mu_H, \mu_A, and \mu_B be empirical measures of eigenvalues of matrices H, A, and B, respectively. Then, it is known (see, for example, Pastur-Vasilchuk, CMP, 2000, v.214, pp.249-286) that for large N, measure \mu_H is close to the free convolution of measures \mu_A and \mu_B, where the free convolution is a non-linear operation on probability measures. The large deviations of the cumulative distribution function of \mu_H from its expectation have been studied by Chatterjee in in JFA, 2007, v. 245, pp.379-389. In this paper we improve Chatterjee's concentration inequality and show that it holds with the rate which is quadratic in N. In addition, we prove a local law for eigenvalues of H, by showing that the normalized number of eigenvalues in an interval converges to the density of the free convolution of \mu_A and \mu_B provided that the interval has width (log N)^{-1/2}.
No associations
LandOfFree
A concentration inequality and a local law for the sum of two random matrices does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with A concentration inequality and a local law for the sum of two random matrices, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and A concentration inequality and a local law for the sum of two random matrices will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-519748