We prove the universality of covariance matrices of the form where is a rectangular matrix with independent real valued entries satisfying and , . Furthermore it is assumed that these entries have sub-exponential tails. We will study the asymptotics in the regime . Our main result states that the Stieltjes transform of the empirical eigenvalue distribution of is given by the Marcenko-Pastur (MP) law uniformly with an error of order where is the imaginary part of the spectral parameter. From this strong local MP law, we derive the following results. 1. The \emph{rigidity of eigenvalues}: If denotes the {\it classical location} of the -th e.v. under the MP law ordered in increasing order, then the -th eigenvalue of is close to such that, P(\exists j: |\lambda_j-\gamma_j| \ge (\log N)^{C\log\log N} [\min \big (\,\min(N,M) - j,j \big) ]^{-1/3} N^{-2/3}) \le C\exp{\big[-(\log N)^{c\log\log N} \big]} 2. The delocalization of the eigenvectors of the matrix uniformly both at the edge and the bulk. 3. Bulk universality, i.e., -point correlation functions of the e.v. of coincide with those of the Wishart ensemble, when goes to infinity. 4. Universality of the eigenvalues of the sample covariance matrix at \emph{both} edges of the spectrum. Furthermore the first two results are applicable even in the case in which the entries of the column vectors of are not independent but satisfy a certain large deviation principle. All our results hold for both real and complex valued entries.
View on arXiv