English

The average singular value of a complex random matrix decreases with dimension

Probability 2023-03-08 v3 Information Theory Classical Analysis and ODEs math.IT

Abstract

We obtain a recurrence relation in dd for the average singular value % \alpha (d) of a complex valued d×dd\times d\ matrix 1dX\frac{1}{\sqrt{d}}X with random i.i.d., N( 0,1) entries, and use it to show that α(d)\alpha (d) decreases monotonically with dd to the limit given by the Marchenko-Pastur distribution.\ The monotonicity of α(d)\alpha (d) has been recently conjectured by Bandeira, Kennedy and Singer in their study of the Little Grothendieck problem over the unitary group Ud\mathcal{U}_{d} \cite{BKS}, a combinatorial optimization problem. The result implies sharp global estimates for α(d)\alpha (d), new bounds for the expected minimum and maximum singular values, and a lower bound for the ratio of the expected maximum and the expected minimum singular value. The proof is based on a connection with the theory of Tur\'{a}n determinants of orthogonal polynomials. We also discuss some applications to the problem that originally motivated the conjecture.

Keywords

Cite

@article{arxiv.1606.00494,
  title  = {The average singular value of a complex random matrix decreases with dimension},
  author = {Luís Daniel Abreu},
  journal= {arXiv preprint arXiv:1606.00494},
  year   = {2023}
}

Comments

The estimate in Lemma 1 is wrong. This invalidates the result. Quoting v1, the error is in the substitution of the first entry of the hypergeometric 3F2, formula (3.3)). Proposition 1 is correct (the - sign is a typo, see (2.1)) and reduces the estimation to only two integrals, but despite several attempts I could not find the required estimate. This has not been published

R2 v1 2026-06-22T14:15:28.583Z