Random subsets of structured deterministic frames have MANOVA spectra [Applied Mathematics]

We draw a random subset of kk rows from a frame with nn rows (vectors) and mm columns (dimensions), where kk and mm are proportional to nn. For a variety of important deterministic equiangular tight frames (ETFs) and tight non-ETFs, we consider the distribution of singular values of the kk-subset matrix. We observe that, for large nn, they can be precisely described by a known probability distribution—Wachter’s MANOVA (multivariate ANOVA) spectral distribution, a phenomenon that was previously known only for two types of random frames. In terms of convergence to this limit, the kk-subset matrix from all of these frames is shown to be empirically indistinguishable from the classical MANOVA (Jacobi) random matrix ensemble. Thus, empirically, the MANOVA ensemble offers a universal description of the spectra of randomly selected kk subframes, even those taken from deterministic frames. The same universality phenomena is shown to hold for notable random frames as well. This description enables exact calculations of properties of solutions for systems of linear equations based on a random choice of kk frame vectors of nn possible vectors and has a variety of implications for erasure coding, compressed sensing, and sparse recovery. When the aspect ratio m/nm/n is small, the MANOVA spectrum tends to the well-known Marčenko–Pastur distribution of the singular values of a Gaussian matrix, in agreement with previous work on highly redundant frames. Our results are empirical, but they are exhaustive, precise, and fully reproducible.