Abstract

We show that every matrix A∈Rn×nA \in \mathbb{R}^{n\times n} is at least δδ∥A∥\|A\|-close to a real matrix A+E∈Rn×nA+E \in \mathbb{R}^{n\times n} whose eigenvectors have condition number at most O~n(δ−1)\tilde{O}_{n}(δ^{-1}). In fact, we prove that, with high probability, taking EE to be a sufficiently small multiple of an i.i.d. real sub-Gaussian matrix of bounded density suffices. This essentially confirms a speculation of Davies, and of Banks, Kulkarni, Mukherjee, and Srivastava, who recently proved such a result for i.i.d. complex Gaussian matrices. Along the way, we also prove non-asymptotic estimates on the minimum possible distance between any two eigenvalues of a random matrix whose entries have arbitrary means; this part of our paper may be of independent interest.

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