Universality for the largest eigenvalue of sample covariance matrices with general population
Zhigang Bao, Guangming Pan, Wang Zhou

TL;DR
This paper establishes the universality of the largest eigenvalue's distribution for high-dimensional sample covariance matrices with general population covariance, extending Tracy-Widom limits to broader settings.
Contribution
It proves the universality of the largest eigenvalue's distribution for general covariance matrices, extending Tracy-Widom laws beyond classical assumptions.
Findings
Largest eigenvalue converges to Tracy-Widom distribution in complex case.
In the real case, spiked covariance matrices follow Tracy-Widom law.
Universality holds under broad distributional assumptions for matrix entries.
Abstract
This paper is aimed at deriving the universality of the largest eigenvalue of a class of high-dimensional real or complex sample covariance matrices of the form . Here, is an random matrix with independent entries such that , . On dimensionality, we assume that and as . For a class of general deterministic positive-definite matrices , under some additional assumptions on the distribution of 's, we show that the limiting behavior of the largest eigenvalue of is universal, via pursuing a Green function comparison strategy raised in [Probab. Theory Related Fields 154 (2012) 341-407, Adv. Math. 229 (2012) 1435-1515] by Erd\H{o}s,…
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