Publication | Open Access
Universality of random matrices with correlated entries
34
Citations
35
References
2017
Year
Spectral TheoryLarge DeviationsEngineeringReal Symmetric RandomMatrix TheoryFunctional AnalysisRandom Matrix TheoryIntegrable ProbabilityStochastic GeometryStatisticsRandom MatricesProbability TheoryFree ProbabilityEntropyStochastic CalculusMarkov KernelProbability MeasureRandom MatrixEigenvalue Statistics
We consider an $N$ by $N$ real symmetric random matrix $X=(x_{ij})$ where $\mathbb{E} [x_{ij}x_{kl}]=\xi _{ijkl}$. Under the assumption that $(\xi _{ijkl})$ is the discretization of a piecewise Lipschitz function and that the correlation is short-ranged we prove that the empirical spectral measure of $X$ converges to a probability measure. The Stieltjes transform of the limiting measure can be obtained by solving a functional equation. Under the slightly stronger assumption that $(x_{ij})$ has a strictly positive definite covariance matrix, we prove a local law for the empirical measure down to the optimal scale $\operatorname{Im} z \gtrsim N^{-1}$. The local law implies delocalization of eigenvectors. As another consequence we prove that the eigenvalue statistics in the bulk agrees with that of the GOE.
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