TheoremBase

Mean-Square Stability of the Optimal Map of a Uniquely Mapped Pair Along Couplings of Nearly Optimal Cost

If a pair of measures with finite second moment is uniquely mapped, then along any sequence of couplings whose quadratic costs tend to the squared Wasserstein distance the mean-square discrepancy between the second coordinate and the image of the first under the optimal map tends to zero.

Statement

In the setting of Probability Measures on Euclidean Space and Random Vectors: Standing Notation, let d∈Nd\in\mathbb{N} satisfy 1≤d1\le d and let μ,ν\mu,\nu belong to the set P2(Rd)\mathcal{P}_{2}(\mathbb{R}^{d}) of probability measures with finite second moment, the second moment of ν\nu being written M2(ν)M_{2}(\nu). Let Π(μ,ν)\Pi(\mu,\nu) be the set of their couplings, let II be the quadratic cost, and let W2(μ,ν)W_{2}(\mu,\nu) be the quadratic Wasserstein distance. Suppose that the ordered pair (μ,ν)(\mu,\nu) is uniquely mapped, and let T:Rd→RdT:\mathbb{R}^{d}\to\mathbb{R}^{d} be an optimal map from μ\mu to ν\nu.

For π∈Π(μ,ν)\pi\in\Pi(\mu,\nu) the function

DT(z)=∥T(pr1(z))−pr2(z)∥2(z∈Rd+d)D_{T}(z)=\bigl\lVert T(\mathrm{pr}_{1}(z))-\mathrm{pr}_{2}(z)\bigr\rVert^{2}\qquad(z\in\mathbb{R}^{d+d})

is Borel and nonnegative by Pairs of Euclidean Points: Coordinate Projections, Pairings, the Product Measure on a Euclidean Space, Borel Norm Functions and Finite Sets (iv), applied to the Borel maps T∘pr1T\circ\mathrm{pr}_{1} and pr2\mathrm{pr}_{2}, and ∫Rd+dDT dπ\int_{\mathbb{R}^{d+d}}D_{T}\,d\pi is a real number not exceeding 4M2(ν)4M_{2}(\nu): by the inequality ∥a−b∥2≤2∥a∥2+2∥b∥2\lVert a-b\rVert^{2}\le2\lVert a\rVert^{2}+2\lVert b\rVert^{2} of Pairs of Euclidean Points: Coordinate Projections, Pairings, the Product Measure on a Euclidean Space, Borel Norm Functions and Finite Sets (iv) it is dominated by 2∥T(pr1(z))∥2+2∥pr2(z)∥22\lVert T(\mathrm{pr}_{1}(z))\rVert^{2}+2\lVert\mathrm{pr}_{2}(z)\rVert^{2}, whose integral against π\pi is 2M2(ν)+2M2(ν)2M_{2}(\nu)+2M_{2}(\nu) by the change-of-variables formula together with (pr1)#π=μ(\mathrm{pr}_{1})_{\#}\pi=\mu, (pr2)#π=ν(\mathrm{pr}_{2})_{\#}\pi=\nu and T#μ=νT_{\#}\mu=\nu.

1. (Mean-square stability) Let (πn)n∈N(\pi_{n})_{n\in\mathbb{N}} be a sequence in Π(μ,ν)\Pi(\mu,\nu) such that (I(πn))n∈N(I(\pi_{n}))_{n\in\mathbb{N}} converges to W2(μ,ν)2W_{2}(\mu,\nu)^{2}. Then the sequence of real numbers (∫Rd+dDT dπn)n∈N\bigl(\int_{\mathbb{R}^{d+d}}D_{T}\,d\pi_{n}\bigr)_{n\in\mathbb{N}} converges to 00.

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