Markov type and threshold embeddings

TL;DR

This paper establishes that threshold-embeddings into Hilbert spaces imply Markov type 2 for metric spaces, leading to new insights on the structure of planar, doubling, and certain Banach space metrics.

Contribution

It proves that threshold-embeddings into Hilbert spaces imply Markov type 2, extending to p-uniformly smooth Banach spaces and providing non-linear analogs of Kwapien's theorem.

Findings

Planar graph metrics have Markov type 2

Doubling metrics have Markov type 2

Threshold-embeddings characterize Markov type 2 in subsets of L1

Abstract

For two metric spaces X and Y, say that X {threshold-embeds} into Y if there exist a number K > 0 and a family of Lipschitz maps $f_{\tau} : X \to Y : \tau > 0 \}$ such that for every $x,y \in X$, \[ d_X(x,y) \geq \tau => d_Y(f_{\tau}(x),f_{\tau}(y)) \geq \|\varphi_{\tau}\|_{\Lip} \tau/K \] where $\|f_{\tau}\|_{\Lip}$ denotes the Lipschitz constant of $f_{\tau}$. We show that if a metric space X threshold-embeds into a Hilbert space, then X has Markov type 2. As a consequence, planar graph metrics and doubling metrics have Markov type 2, answering questions of Naor, Peres, Schramm, and Sheffield. More generally, if a metric space X threshold-embeds into a p-uniformly smooth Banach space, then X has Markov type p. This suggests some non-linear analogs of Kwapien's theorem. For instance, a subset $X \subseteq L_1$ threshold-embeds into Hilbert space if and only if X has Markov type 2.