Marchenko-Pastur law for tensor powers of exchangeable unconditional vectors

Given an isotropic, exchangeable, and unconditional random vector $\mathbf{X}$, we consider the sample covariance matrix constructed from i.i.d. copies of several tensor models of $\mathbf{X}$, such as the tensor power ${\mathbf{X}}^{\otimes d}$. Under appropriate moment conditions on $\mathbf{X}$, 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 $\mathbf{X}$ to be independent. As we demonstrate, our extension applies to many new random vectors $\mathbf{X}$ of interest.