Marchenko-Pastur law for tensor powers of exchangeable unconditional vectors
Probability
2026-07-23 v1 Statistics Theory
Abstract
Given an isotropic, exchangeable, and unconditional random vector , we consider the sample covariance matrix constructed from i.i.d. copies of several tensor models of , such as the tensor power . Under appropriate moment conditions on , we show that almost surely, the empirical spectral distribution converges weakly to the Marchenko-Pastur law. This extends previous results which required the coordinates of to be independent. As we demonstrate, our extension applies to many new random vectors of interest.
Keywords
Cite
@article{arxiv.2607.21759,
title = {Marchenko-Pastur law for tensor powers of exchangeable unconditional vectors},
author = {Feng Cheng and Dan Mikulincer},
journal= {arXiv preprint arXiv:2607.21759},
year = {2026}
}
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33 pages