Real spectra of large asymmetric Gaussian random matrices

Real spectra of large asymmetric Gaussian random matrices

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Gaussian random matrices play a central role in random matrix theory, serving as canonical models whose spectral properties often persist across much broader classes of ensembles. Many observables in non-Gaussian settings—including the limiting spectrum, local correlation functions, and counting statistics—exhibit the same asymptotic behavior as in the Gaussian case. In this talk, we briefly review the importance of Gaussian random matrices. We then focus on the real eigenvalues of asymmetric Gaussian random matrices, and discuss recent progress on their statistical properties.