Euclidean embedding, randomized clustering, and Lipschitz extension for finite and doubling subsets of $L_p$ when $p>2$
Abstract
Fix . We prove that the Euclidean distortion of every -point subset of is , thus, in particular, demonstrating that all -point subsets of exhibit an asymptotic improvement over the Euclidean distortion guarantee that Bourgain's embedding theorem provides for arbitrary -point metric spaces. We also prove that the separation modulus of every -point subset of is , which is sharp up to the dependence on . We deduce from (a refinement of) this asymptotic evaluation of the finitary separation modulus of that for any -point subset of , any Banach space , and any -Lipschitz function , there exists a -Lipschitz function that extends . We obtain analogous separation and extension statements for doubling subsets of .
Keywords
Cite
@article{arxiv.2502.10543,
title = {Euclidean embedding, randomized clustering, and Lipschitz extension for finite and doubling subsets of $L_p$ when $p>2$},
author = {Assaf Naor and Kevin Ren},
journal= {arXiv preprint arXiv:2502.10543},
year = {2026}
}
Comments
Published version on Ars Inveniendi Analytica (2026)