Optimal Ballistic Transport and Hopf-Lax Formulae on Wasserstein Space

TL;DR

This paper extends classical optimal transport and Hopf-Lax formulae to Wasserstein space for a ballistic cost functional, establishing connections with mean field games and providing new insights into transport maps.

Contribution

It introduces a novel approach to lift Hopf-Lax formulae to Wasserstein space using convex duality, relating ballistic and fixed-end costs in optimal transport.

Findings

Established a duality-based framework for ballistic cost transport

Connected ballistic transport maps to classical fixed-end cost maps

Linked the theory to mean field games

Abstract

We investigate the optimal mass transport problem associated to the following "ballistic" cost functional on phase space $M\times M^*$, $$ b_T(v, x):=\inf\{\langle v, \gamma (0)\rangle +\int_0^TL(\gamma (t), {\dot \gamma}(t))\, dt, \gamma \in C^1([0, T), M), \gamma(T)=x\}, $$ where $M=\mathbb{R}^d$, $T>0$, and $L:M\times M \to \mathbb{R}$ is a Lagrangian that is jointly convex in both variables. Under suitable conditions on the initial and final probability measures, we use convex duality \`a la Bolza and Monge-Kantorovich theory to lift classical Hopf-Lax formulae from state space to Wasserstein space. This allows us to relate optimal transport maps for the ballistic cost to those associated with the fixed-end cost defined on $M\times M$ by $$ c_T(x,y):=\inf\{\int_0^TL(\gamma(t), {\dot \gamma}(t))\, dt, \gamma\in C^1([0, T), M), \gamma(0)=x, \gamma(T)=y\}. $$ We also point to links with the theory of mean field games.