A View on Optimal Transport from Noncommutative Geometry

TL;DR

This paper explores the relationship between Wasserstein and spectral distances in both classical and noncommutative geometries, providing explicit computations and bounds, and highlighting the implications for models like the standard model and Moyal plane.

Contribution

It establishes conditions under which Wasserstein and spectral distances coincide on Riemannian manifolds and extends the analogy to noncommutative spaces, introducing new interpretations of the metric.

Findings

Distances coincide on complete Riemannian spin manifolds.

Bounds are provided for convex manifolds in Nash embedding.

Explicit distance computations for generalized Gaussian distributions.

Abstract

We discuss the relation between the Wasserstein distance of order 1 between probability distributions on a metric space, arising in the study of Monge-Kantorovich transport problem, and the spectral distance of noncommutative geometry. Starting from a remark of Rieffel on compact manifolds, we first show that on any - i.e. non-necessary compact - complete Riemannian spin manifolds, the two distances coincide. Then, on convex manifolds in the sense of Nash embedding, we provide some natural upper and lower bounds to the distance between any two probability distributions. Specializing to the Euclidean space $R^n$, we explicitly compute the distance for a particular class of distributions generalizing Gaussian wave packet. Finally we explore the analogy between the spectral and the Wasserstein distances in the noncommutative case, focusing on the standard model and the Moyal plane. In particular we point out that in the two-sheet space of the standard model, an optimal-transport interpretation of the metric requires a cost function that does not vanish on the diagonal. The latest is similar to the cost function occurring in the relativistic heat equation.