English

Dimension-free cotype for isotropic log-concave random polytope spaces

Functional Analysis 2026-07-11 v1 Metric Geometry Probability

Abstract

Let X1,,XNX_1,\ldots,X_N be independent random vectors in Rn\mathbb{R}^n with common isotropic log-concave distribution μ\mu and set PN,nμ:=conv{±Xi:1iN}P_{N,n}^{\mu}:=\operatorname{conv}\{\pm X_i:1\leqslant i\leqslant N\}. Assume that N/n=γγ0N/n=\gamma\geqslant \gamma_0 where γ0>1\gamma_0>1 is an absolute constant. We prove that with probability at least 1Cγexp(cn1/4)1-C\gamma\exp(-c n^{1/4}) every kk-dimensional subspace EE of (Rn,PN,nμ)(\mathbb{R}^n,\|\cdot\|_{P_{N,n}^{\mu}}) satisfies dBM(E,k)cγCkαd_{\mathrm{BM}} (E,\ell_\infty^k) \geqslant c\gamma^{-C}k^\alpha for every 1kn1\leqslant k\leqslant n where c,C,α>0c,C,\alpha>0 are absolute constants. Consequently, with the same probability, (Rn,PN,nμ)(\mathbb{R}^n,\|\cdot\|_{P_{N,n}^{\mu}}) has cotype q(γ)<q(\gamma)<\infty with cotype constant depending only on γ\gamma, in particular the cotype exponent and the cotype constant are independent of nn and of μ\mu. The proof adapts the deterministic coefficient scheme of Huang-Tikhomirov replacing the Gaussian estimates in their argument by estimates for isotropic log-concave random matrices. As an application, using the log-concave extension of Gluskin's theorem, we obtain a separable Banach space of finite cotype for which the Banach-Mazur diameter of its kk-dimensional subspaces is of order kk and whose finite-dimensional building blocks are generated by isotropic log-concave random polytopes.

Cite

@article{arxiv.2607.10373,
  title  = {Dimension-free cotype for isotropic log-concave random polytope spaces},
  author = {Antonios Hmadi},
  journal= {arXiv preprint arXiv:2607.10373},
  year   = {2026}
}