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Proof of A Displacement Convex Penalty Pair Has a Monotone Score Along Optimally Coupled Pairs

lemmalem:displacement-convex-pair-monotone-2026c
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· 3,167 chars · 10 deps · depth 34 Reason: New proof for the lifted statement: the reversed pair is optimally coupled, two applications of displacement convexity, bilinearity.

The reversed pair is again optimally coupled, by symmetry of the mean-square distance and of the Wasserstein distance; adding the two displacement-convexity inequalities cancels the penalties, and bilinearity of the inner product gives the claim.

Proof

Each result cited is universally quantified over the data in its own statement and is applied here to the data named in the statement of the lemma. Write μ=L(X)\mu=\mathcal{L}(X) and ν=L(Y)\nu=\mathcal{L}(Y), both in DΣ\mathcal{D}_{\Sigma}, hence in D\mathcal{D} by Penalty Pairs on the Wasserstein Space: the Penalty, Its Score, and Their Domains §pair, so that E(μ)\mathcal{E}(\mu) and E(ν)\mathcal{E}(\nu) are real numbers; write σX=Σ(μ)X\sigma_{X}=\Sigma(\mu)\circ X and σY=Σ(ν)Y\sigma_{Y}=\Sigma(\nu)\circ Y, elements of L2(Ω;Rd)L^{2}(\Omega;\mathbb{R}^{d}) by Composition of a Square-Integrable Vector Field with a Random Vector, and the Lifted Score: Isometry, Norm, Weak Identity and Second-Moment Identity §composition. The space L2(Ω;Rd)L^{2}(\Omega;\mathbb{R}^{d}) is a real Hilbert space by Wasserstein Spaces, Random Vectors, Vector Fields and Symmetric Matrices in Every Dimension: Standing Notation §dimensions, so Elementary Identities in a Real Inner Product Space and The Norm Metric of a Real Inner Product Space: Triangle Inequalities, Limits and Continuity apply to it with the norm L2\lVert\cdot\rVert_{L^{2}}; real arithmetic is that of the field axioms of Field and of Elementary Arithmetic in an Ordered Field.

The reversed pair is optimally coupled. By Optimally Coupled Pairs of Square-Integrable Random Vectors §optimal, XYL22=W2(μ,ν)2\lVert X-Y\rVert_{L^{2}}^{2}=W_{2}(\mu,\nu)^{2}. By The Norm Metric of a Real Inner Product Space: Triangle Inequalities, Limits and Continuity §metric the function dL2(Z,Z)=ZZL2d_{L^{2}}(Z,Z')=\lVert Z-Z'\rVert_{L^{2}} is a metric, hence symmetric, so YXL2=XYL2\lVert Y-X\rVert_{L^{2}}=\lVert X-Y\rVert_{L^{2}}; and W2(ν,μ)=W2(μ,ν)W_{2}(\nu,\mu)=W_{2}(\mu,\nu) by The Quadratic Wasserstein Distance is a Metric on the Wasserstein Space §symmetry. Hence YXL22=W2(ν,μ)2\lVert Y-X\rVert_{L^{2}}^{2}=W_{2}(\nu,\mu)^{2}, that is, (Y,X)(Y,X) is optimally coupled by Optimally Coupled Pairs of Square-Integrable Random Vectors §optimal.

Two applications of displacement convexity. Since (X,Y)(X,Y) is optimally coupled with μDΣ\mu\in\mathcal{D}_{\Sigma} and νD\nu\in\mathcal{D}, and (Y,X)(Y,X) is optimally coupled with νDΣ\nu\in\mathcal{D}_{\Sigma} and μD\mu\in\mathcal{D}, Displacement Convexity of a Penalty Pair on the Wasserstein Space §convex gives

E(μ)+σX,YXL2E(ν)andE(ν)+σY,XYL2E(μ).\mathcal{E}(\mu)+\langle\sigma_{X},Y-X\rangle_{L^{2}}\le\mathcal{E}(\nu)\qquad\text{and}\qquad\mathcal{E}(\nu)+\langle\sigma_{Y},X-Y\rangle_{L^{2}}\le\mathcal{E}(\mu).

By claim 3 of Elementary Arithmetic in an Ordered Field, 0E(ν)E(μ)σX,YXL20\le\mathcal{E}(\nu)-\mathcal{E}(\mu)-\langle\sigma_{X},Y-X\rangle_{L^{2}} and 0E(μ)E(ν)σY,XYL20\le\mathcal{E}(\mu)-\mathcal{E}(\nu)-\langle\sigma_{Y},X-Y\rangle_{L^{2}}, and by claim 2 of that lemma the sum of these two nonnegative numbers is nonnegative; the terms E(μ)\mathcal{E}(\mu) and E(ν)\mathcal{E}(\nu) cancel in the sum by the field axioms, so

0σX,YXL2σY,XYL2.0\le-\langle\sigma_{X},Y-X\rangle_{L^{2}}-\langle\sigma_{Y},X-Y\rangle_{L^{2}}.

Rewriting the right-hand side. By Elementary Identities in a Real Inner Product Space §bilinear, σX,YXL2=σX,YL2σX,XL2\langle\sigma_{X},Y-X\rangle_{L^{2}}=\langle\sigma_{X},Y\rangle_{L^{2}}-\langle\sigma_{X},X\rangle_{L^{2}} and σX,XYL2=σX,XL2σX,YL2\langle\sigma_{X},X-Y\rangle_{L^{2}}=\langle\sigma_{X},X\rangle_{L^{2}}-\langle\sigma_{X},Y\rangle_{L^{2}}, so σX,YXL2=σX,XYL2-\langle\sigma_{X},Y-X\rangle_{L^{2}}=\langle\sigma_{X},X-Y\rangle_{L^{2}} by the field axioms. Therefore, again by Elementary Identities in a Real Inner Product Space §bilinear in the first argument,

0σX,XYL2σY,XYL2=σXσY,XYL2,0\le\langle\sigma_{X},X-Y\rangle_{L^{2}}-\langle\sigma_{Y},X-Y\rangle_{L^{2}}=\langle\sigma_{X}-\sigma_{Y},X-Y\rangle_{L^{2}},

which is the claim.

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