Optimal transport between laws of random probability measures and the strict Monge problem

TL;DR

This paper explores optimal transport between laws of random probability measures, characterizing optimal solutions and establishing conditions for uniqueness and Monge solutions, extending classical results to a more complex probabilistic setting.

Contribution

It introduces a novel optimal transport framework for laws of random measures, characterizes optimal couplings via Kantorovich potentials, and links the problem to a strict Monge formulation with uniqueness results.

Findings

Characterization of optimal couplings via Kantorovich potentials.

Conditions under which the strict Monge problem's value matches the original.

Uniqueness of optimal random couplings in certain Banach space settings.

Abstract

We consider an optimal transport problem between laws of random probability measures: given a base cost function, we build the associated OT cost between probability measures that in turn we use to define the OT cost between probability measures over probability measures. This setting admits a finer reformulation in terms of laws of random couplings, which retain more information than ordinary couplings. One of the main contributions of the paper is the characterization of the optimal ones in terms of Kantorovich potentials. Similarly, we also introduce the strict Monge problem, whose admissible competitors are more restrictive than in the usual Monge formulation. In this setting, we will give sufficient conditions under which the value of this problem is the same as the one considered above, in the spirit of the result by A. Pratelli. Then, for $p>1$, when the underlying cost is the distance to the power $p$ in a strictly convex Banach space, we will give sufficient conditions under which the optimal random coupling is unique and induced by a solution of the strict Monge problem, resembling the Brenier theorem.