Authors: Terence Tao
Publish Date: 2011/11/03
Volume: 155, Issue: 1-2, Pages: 231-263
Abstract
It is known that if one perturbs a large iid random matrix by a bounded rank error then the majority of the eigenvalues will remain distributed according to the circular law However the bounded rank perturbation may also create one or more outlier eigenvalues We show that if the perturbation is small then the outlier eigenvalues are created next to the outlier eigenvalues of the bounded rank perturbation but if the perturbation is large then many more outliers can be created and their law is governed by the zeroes of a random Laurent series with Gaussian coefficients On the other hand these outliers may be eliminated by enforcing a row sum condition on the final matrix
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