We consider certain large random matrices, called random inner-product kernel matrices, which are essentially given by a nonlinear function applied entrywise to a sample-covariance matrix, , where is random and normalized in such a way that typically has order-one arguments. We work in the polynomial regime, where for some , not just the linear regime where . Earlier work by various authors showed that, when the columns of are either uniform on the sphere or standard Gaussian vectors, and when is an integer (the linear regime 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 in the Hermite basis. In this paper, we show that this phenomenon is universal, holding as soon as has i.i.d. entries with all finite moments. In the case of non-integer , the Mar\v{c}enko-Pastur term disappears (its weight in the free convolution vanishes), and the spectrum is just semicircular.
View on arXiv