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Dynamical Optimal Transport with \mathfrakso(d)-Invariance: From Theory to Computation

2026/07/18 by Kevine Meugang Toukam, Max von Renesse, Johannes Storn
#math.OC

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Abstract

We introduce a modified Benamou--Brenier (MBB) formulation of optimal transport that incorporates Euclidean invariance at the dynamical level. We establish existence of minimizers for the resulting variational problem and prove its equivalence to a static formulation defining the Procrustes--Wasserstein distance. In the Gaussian setting, we show that this distance admits a closed-form expression, reducing to the Euclidean distance between the vectors of square roots of the ordered eigenvalues of the covariance matrices. On the computational side, we formulate a primal--dual scheme for the discretized problem. We prove a local conditional subsequential convergence result through an abstract analysis of a class of parameter-dependent saddle-point problems and illustrate the method's performance numerically.

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