Smoothing inequalities for transport metrics in compact spaces

TL;DR

This paper establishes upper bounds for Wasserstein distances between probability measures on compact manifolds using Fourier analysis, covering the full range of p and applying to spherical designs.

Contribution

It provides the first comprehensive bounds for Wasserstein metrics on compact manifolds for all p, linking Fourier transforms and Sobolev norms.

Findings

Derived upper bounds for Wasserstein distances on compact manifolds.

Extended analysis to the full range of p in Wasserstein metrics.

Showed spherical designs are near optimal in Wasserstein distance.

Abstract

We prove general upper estimates for the distance between two Borel probability measures in Wasserstein metric in terms of the Fourier transforms of the measures. We work in compact manifolds including the torus, the Euclidean unit sphere, compact Lie groups and compact homogeneous spaces, and treat the Wasserstein metric $W_p$ in the full range $1 \le p \le \infty$ for the first time. The proofs are based on a comparison between the Wasserstein metric and a dual Sobolev norm, Riesz transform estimates and Hausdorff--Young inequalities on compact manifolds. As an application, we show that spherical designs are optimally close to the uniform measure on the sphere in Wasserstein metric.