Real eigenvalues of non-symmetric random matrices: Transitions and Universality

preprint2016arXivOpen access

Abstract

In the past 20 years, the study of real eigenvalues of non-symmetric real random matrices has seen important progress. Notwithstanding, central questions still remain open, such as the characterization of their asymptotic statistics and the universality thereof. In this letter we show that for a wide class of matrices, the number knk_n of real eigenvalues of a matrix of size nn is asymptotically Gaussian with mean kˉn=O(n)\bar k_n=\mathcal{O}(\sqrt{n}) and variance kˉn(2−2)\bar k_n(2-\sqrt{2}). Moreover, we show that the limit distribution of real eigenvalues undergoes a transition between bimodal for kn=o(n)k_n=o(\sqrt{n}) to unimodal for kn=O(n)k_n=\mathcal{O}(n), with a uniform distribution at the transition. We predict theoretically these behaviours in the Ginibre ensemble using a log-gas approach, and show numerically that they hold for a wide range of random matrices with independent entries beyond the universality class of the circular law.

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