Formal Riemannian Structure of the Wasserstein metric

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Given a closed and convex space , two probability measures on the same space, , the 2-Wasserstein metric is defined as

where is a transport plan from to . The Wasserstein metric is indeed a metric in the sense that it satisfies the desired properties of a distance function between probability measures on . Moreover, the Wasserstein metric can be used to define a Riemannian metric on . Such a metric allows one to define angles and lengths of vectors at each point in our ambient space.

Tangent Space Induced by the Wasserstein Metric

A convenient way to formalize tangent vectors in this setting is to consider time derivatives of curves on the manifold. A tangent vector at a point would be the time derivative at 0 of a curve, , where [1]. Since we are dealing with a space of probability measures, additional restrictions need to be added in order to make our tangent space well-defined. For example, we would like our trajectory to satisfy the continuity equation . There are many such vector fields that solve the continuity equation, so we can restrict to a vector field that minimizes kinetic energy, which is defined as . This choice of tangent vectors is justified by the following lemma

Lemma[2] A vector belongs to the tangent cone at iff

where we are taking the norm. Divergence condition implies that our tangent vectors are equivalent up to a vector field with zero divergence. This implies that is in fact a gradient of some function , in which case our continuity equation becomes

Riemannian Metric Induced by the Wasserstein Metric

References

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