English

Condition Numbers of Gaussian Random Matrices

Numerical Analysis 2008-10-07 v1

Abstract

Let Gm×nG_{m \times n} be an m×nm \times n real random matrix whose elements are independent and identically distributed standard normal random variables, and let κ2(Gm×n)\kappa_2(G_{m \times n}) be the 2-norm condition number of Gm×nG_{m \times n}. We prove that, for any m2m \geq 2, n2n \geq 2 and xnm+1x \geq |n-m|+1, κ2(Gm×n)\kappa_2(G_{m \times n}) satisfies 12π(c/x)nm+1<P(κ2(Gm×n)n/(nm+1)>x)<12π(C/x)nm+1, \frac{1}{\sqrt{2\pi}} ({c}/{x})^{|n-m|+1} < P(\frac{\kappa_2(G_{m \times n})} {{n}/{(|n-m|+1)}}> x) < \frac{1}{\sqrt{2\pi}} ({C}/{x})^{|n-m|+1}, where 0.245c2.0000.245 \leq c \leq 2.000 and 5.013C6.414 5.013 \leq C \leq 6.414 are universal positive constants independent of mm, nn and xx. Moreover, for any m2m \geq 2 and n2n \geq 2, E(logκ2(Gm×n))<lognnm+1+2.258. E(\log\kappa_2(G_{m \times n})) < \log \frac{n}{|n-m|+1} + 2.258. A similar pair of results for complex Gaussian random matrices is also established.

Cite

@article{arxiv.0810.0800,
  title  = {Condition Numbers of Gaussian Random Matrices},
  author = {Zizhong Chen and Jack Dongarra},
  journal= {arXiv preprint arXiv:0810.0800},
  year   = {2008}
}
R2 v1 2026-06-21T11:27:24.814Z