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Universality for the global spectrum of random inner-product kernel matrices in the polynomial regime

27 October 2023
S. Dubova
Yue M. Lu
Benjamin McKenna
H. Yau
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Abstract

We consider certain large random matrices, called random inner-product kernel matrices, which are essentially given by a nonlinear function fff applied entrywise to a sample-covariance matrix, f(XTX)f(X^TX)f(XTX), where X∈Rd×NX \in \mathbb{R}^{d \times N}X∈Rd×N is random and normalized in such a way that fff typically has order-one arguments. We work in the polynomial regime, where N≍dℓN \asymp d^\ellN≍dℓ for some ℓ>0\ell > 0ℓ>0, not just the linear regime where ℓ=1\ell = 1ℓ=1. Earlier work by various authors showed that, when the columns of XXX are either uniform on the sphere or standard Gaussian vectors, and when ℓ\ellℓ is an integer (the linear regime ℓ=1\ell = 1ℓ=1 is particularly well-studied), the bulk eigenvalues of such matrices behave in a simple way: They are asymptotically given by the free convolution of the semicircular and Mar\v{c}enko-Pastur distributions, with relative weights given by expanding fff in the Hermite basis. In this paper, we show that this phenomenon is universal, holding as soon as XXX has i.i.d. entries with all finite moments. In the case of non-integer ℓ\ellℓ, the Mar\v{c}enko-Pastur term disappears (its weight in the free convolution vanishes), and the spectrum is just semicircular.

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