Search arXivSearch

arXiv · 2112.11523

Extension, separation and isomorphic reverse isoperimetry

Abstract

The Lipschitz extension modulus $e(M)$ of a metric space $M$ is the infimum over $L\ge 1$ such that for any Banach space $Z$ and any $C\subset M$, any 1-Lipschitz function $f:C\to Z$ can be extended to an $L$-Lipschitz function $F:M\to Z$. Johnson, Lindenstrauss and Schechtman proved that if $X$ is an $n$-dimensional normed space, then $e(X)=O(n)$. In the reverse direction, we prove that every $n$-dimensional normed space $X$ satisfies $e(X)\ge n^c$, where $c>0$ is a universal constant. Our core technical contribution is a geometric structural result on stochastic clustering of finite dimensional normed spaces which implies upper bounds on their Lipschitz extension moduli using an extension method of Lee and the author. The separation modulus of a metric space $(M,d_M)$ is the infimum over $σ>0$ such that for any $Δ>0$ there is a distribution over random partitions of $M$ into clusters of diameter at most $Δ$ such that for every $x,y\in M$ the probability that they belong to different clusters is at most $σd_M(x,y)/Δ$. We obtain upper and lower bounds on the separation moduli of finite dimensional normed spaces that relate them to well-studied volumetric invariants. Using these connections, we find the growth rate of the separation moduli of various normed spaces. We formulate a conjecture on isomorphic reverse isoperimetry that can be used with our volumetric bounds on the separation modulus to obtain many more asymptotic evaluations of the separation moduli of normed spaces. Our estimates on the separation modulus imply improved bounds on the Lipschitz extension moduli of various classical spaces. In particular, we deduce an improved bound on $e(\ell_p^n)$ when $p>2$ that resolves a conjecture of Brudnyi and Brudnyi, and prove that $e(\ell_\infty^n)\asymp{\sqrt{n}}$, which is the first time that the order of $e(X)$ has been evaluated for any normed space $X$.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Assaf Naor. 2024-02-12. Extension, separation and isomorphic reverse isoperimetry. https://arxiv.org/abs/2112.11523

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

$β$-Uniform Convexity and Divisible Domains

Divisible convex sets have long been important in the study of Hilbert geometries. When a divisible convex set is an ellipsoid, the Hilbert geometry it induces is the hyperbolic space. In general, strictly convex divisible domains exhibit negative curvature properties, but only the ellipsoid is a CAT(0) space. The notion of p-uniform convexity from the theory of Banach spaces has been proposed by Shin-Ichi Ohta as a generalization of the Alexandrov-Toponogov comparison theorems to Finsler manifolds. We prove that a natural Finsler metric on a strictly convex divisible domain is $β$-uniformly convex, where the constant $β$ is related to the regularity of the boundary. We use this to show, with AI assistance, that the Hilbert metric, under suitable local and scale-dependent assumptions, is $β$-uniformly convex on such domains.

math.MG

A positive solution to the $L^p$ projection centroid conjecture

In a classical paper [21] in 2000, Lutwak-Yang-Zhang established the $L^p$ analog of the Petty projection inequality and the $L^p$ analog of the Busemann-Petty centroid inequality. In Section 7 of [21], Lutwak-Yang-Zhang proposed the important $L^p$ projection centroid conjecture. We give a positive solution to the $L^p$ projection centroid conjecture in this work.

math.MG

Minimal central slices of the regular simplex

We prove that minimal-volume hyperplane sections of the regular simplex through its centroid are parallel to a facet. The proof combines variational methods with Fourier-analytic techniques and zero-diminishing arguments to show that every critical normal vector has at most three distinct non-zero coordinates. Analysis of the two- and three-value cases then yields the sharp lower bound.

math.MG