TheoremBase

Every claim reduces to the identity U(X) = u(L(X)) together with the two halves of the lift lemma: the Wasserstein distance is dominated by the mean-square distance, and on a rich space it is the infimum of the mean-square distances over all realisations.

Proof

Each result cited is universally quantified over the data in its own statement. Throughout, U(X)=u(L(X))U(X)=u(\mathcal{L}(X)) for every X∈L2(Ω;Rd)X\in L^{2}(\Omega;\mathbb{R}^{d}) by The Lift of a Function on the Wasserstein Space to the Space of Square-Integrable Random Vectors (i), and L(X)∈P2(Rd)\mathcal{L}(X)\in\mathcal{P}_{2}(\mathbb{R}^{d}) by The Wasserstein Space and Its Lift to Square-Integrable Random Vectors: Standing Notation (v). The metric on R\mathbb{R} is dR(s,t)=∣s−t∣d_{\mathbb{R}}(s,t)=|s-t| (Real Hilbert Spaces: Standing Notation and Background (i)), so that for real-valued functions the distance between two values is the absolute value of their difference; the metric on L2(Ω;Rd)L^{2}(\Omega;\mathbb{R}^{d}) is dL2(X,Y)=∥X−Y∥L2d_{L^{2}}(X,Y)=\lVert X-Y\rVert_{L^{2}} (The Wasserstein Space and Its Lift to Square-Integrable Random Vectors: Standing Notation (iii)) and that on P2(Rd)\mathcal{P}_{2}(\mathbb{R}^{d}) is W2W_{2} (The Wasserstein Space and Its Lift to Square-Integrable Random Vectors: Standing Notation (iv)). Two facts about the law map are used repeatedly, both from The Wasserstein Space and Its Lift to Square-Integrable Random Vectors: Standing Notation (v): the domination inequality of The Wasserstein Distance and the Mean-Square Distance of Random Vectors (ii), namely, for all X,Y∈L2(Ω;Rd)X,Y\in L^{2}(\Omega;\mathbb{R}^{d}),

W2(L(X),L(Y))≤∥X−Y∥L2,W_{2}(\mathcal{L}(X),\mathcal{L}(Y))\le\lVert X-Y\rVert_{L^{2}} ,

and, when (Ω,F,P)(\Omega,\mathcal{F},P) is rich, every μ∈P2(Rd)\mu\in\mathcal{P}_{2}(\mathbb{R}^{d}) is the law of some X∈L2(Ω;Rd)X\in L^{2}(\Omega;\mathbb{R}^{d}) (The Wasserstein Distance and the Mean-Square Distance of Random Vectors (iii)), and for all μ,ν∈P2(Rd)\mu,\nu\in\mathcal{P}_{2}(\mathbb{R}^{d}) the set D(μ,ν)={∥X−Y∥L2:L(X)=μ, L(Y)=ν}D(\mu,\nu)=\{\lVert X-Y\rVert_{L^{2}}:\mathcal{L}(X)=\mu,\ \mathcal{L}(Y)=\nu\} (the letter DD denoting this set and not a gradient throughout this proof) is nonempty and bounded below with inf⁡D(μ,ν)=W2(μ,ν)\inf D(\mu,\nu)=W_{2}(\mu,\nu) (The Wasserstein Distance and the Mean-Square Distance of Random Vectors (iv)), the infimum being the greatest lower bound.

Claim 1. Let X,Y∈L2(Ω;Rd)X,Y\in L^{2}(\Omega;\mathbb{R}^{d}) with L(X)=L(Y)\mathcal{L}(X)=\mathcal{L}(Y). Then U(X)=u(L(X))=u(L(Y))=U(Y)U(X)=u(\mathcal{L}(X))=u(\mathcal{L}(Y))=U(Y), so UU is law-invariant in the sense of Law-Invariant Function on the Space of Square-Integrable Random Vectors (i).

Claim 2. Let (Ω,F,P)(\Omega,\mathcal{F},P) be rich and let Φ\Phi be law-invariant. Existence. For μ∈P2(Rd)\mu\in\mathcal{P}_{2}(\mathbb{R}^{d}) the set {Φ(X):X∈L2(Ω;Rd), L(X)=μ}\{\Phi(X):X\in L^{2}(\Omega;\mathbb{R}^{d}),\ \mathcal{L}(X)=\mu\} is nonempty by The Wasserstein Distance and the Mean-Square Distance of Random Vectors (iii) and has exactly one element, since Φ(X)=Φ(X′)\Phi(X)=\Phi(X') whenever L(X)=μ=L(X′)\mathcal{L}(X)=\mu=\mathcal{L}(X') by Law-Invariant Function on the Space of Square-Integrable Random Vectors (i); let v(μ)v(\mu) be that element. This defines v:P2(Rd)→Rv:\mathcal{P}_{2}(\mathbb{R}^{d})\to\mathbb{R}, and for every X∈L2(Ω;Rd)X\in L^{2}(\Omega;\mathbb{R}^{d}) the element XX itself has law L(X)\mathcal{L}(X), so v(L(X))=Φ(X)v(\mathcal{L}(X))=\Phi(X); that is, the lift of vv is Φ\Phi. Uniqueness. Let v,v′:P2(Rd)→Rv,v':\mathcal{P}_{2}(\mathbb{R}^{d})\to\mathbb{R} both have lift Φ\Phi and let μ∈P2(Rd)\mu\in\mathcal{P}_{2}(\mathbb{R}^{d}). Choose XX with L(X)=μ\mathcal{L}(X)=\mu by The Wasserstein Distance and the Mean-Square Distance of Random Vectors (iii); then v(μ)=v(L(X))=Φ(X)=v′(L(X))=v′(μ)v(\mu)=v(\mathcal{L}(X))=\Phi(X)=v'(\mathcal{L}(X))=v'(\mu). Hence v=v′v=v'.

Claim 3. Let uu be bounded with bound MM, so that ∣u(μ)∣≤M|u(\mu)|\le M for every μ∈P2(Rd)\mu\in\mathcal{P}_{2}(\mathbb{R}^{d}) by Bounded Real-Valued Function on a Set. For X∈L2(Ω;Rd)X\in L^{2}(\Omega;\mathbb{R}^{d}), ∣U(X)∣=∣u(L(X))∣≤M|U(X)|=|u(\mathcal{L}(X))|\le M; so UU is bounded with bound MM.

Claim 4. Let (Ω,F,P)(\Omega,\mathcal{F},P) be rich and UU bounded with bound MM. For μ∈P2(Rd)\mu\in\mathcal{P}_{2}(\mathbb{R}^{d}) choose XX with L(X)=μ\mathcal{L}(X)=\mu by The Wasserstein Distance and the Mean-Square Distance of Random Vectors (iii); then ∣u(μ)∣=∣U(X)∣≤M|u(\mu)|=|U(X)|\le M. So uu is bounded with bound MM.

Claim 5. Let uu be Lipschitz with constant κ\kappa, so that ∣u(μ)−u(ν)∣≤κ W2(μ,ν)|u(\mu)-u(\nu)|\le\kappa\,W_{2}(\mu,\nu) for all μ,ν∈P2(Rd)\mu,\nu\in\mathcal{P}_{2}(\mathbb{R}^{d}) by Lipschitz Map Between Metric Spaces. For X,Y∈L2(Ω;Rd)X,Y\in L^{2}(\Omega;\mathbb{R}^{d}),

∣U(X)−U(Y)∣=∣u(L(X))−u(L(Y))∣≤κ W2(L(X),L(Y))≤κ ∥X−Y∥L2,|U(X)-U(Y)|=|u(\mathcal{L}(X))-u(\mathcal{L}(Y))|\le\kappa\,W_{2}(\mathcal{L}(X),\mathcal{L}(Y))\le\kappa\,\lVert X-Y\rVert_{L^{2}},

the last step by the domination inequality and claim 5 of Elementary Arithmetic in an Ordered Field (multiplication by the nonnegative κ\kappa), and the two inequalities combine by the transitivity of ≤\le, the order of R\mathbb{R} being that of an ordered field (Real Hilbert Spaces: Standing Notation and Background (i)). So UU is Lipschitz with constant κ\kappa.

Claim 6. Let (Ω,F,P)(\Omega,\mathcal{F},P) be rich and UU Lipschitz with constant κ\kappa, and let μ,ν∈P2(Rd)\mu,\nu\in\mathcal{P}_{2}(\mathbb{R}^{d}); put c=∣u(μ)−u(ν)∣c=|u(\mu)-u(\nu)|. For every s∈D(μ,ν)s\in D(\mu,\nu), say s=∥X−Y∥L2s=\lVert X-Y\rVert_{L^{2}} with L(X)=μ\mathcal{L}(X)=\mu and L(Y)=ν\mathcal{L}(Y)=\nu, we have c=∣U(X)−U(Y)∣≤κ sc=|U(X)-U(Y)|\le\kappa\,s by Lipschitz Map Between Metric Spaces. If κ=0\kappa=0, choose s∈D(μ,ν)s\in D(\mu,\nu), which is nonempty; then c≤κ s=0=κ W2(μ,ν)c\le\kappa\,s=0=\kappa\,W_{2}(\mu,\nu) by claim 1 of Zero Products and Elementary Identities in a Field. If κ≠0\kappa\ne0, then κ−1\kappa^{-1} exists, and 0≤κ−10\le\kappa^{-1} by claim 4 of Elementary Arithmetic in an Ordered Field; multiplying c≤κ sc\le\kappa\,s by κ−1\kappa^{-1} (claim 5 there) gives κ−1c≤κ−1(κ s)=s\kappa^{-1}c\le\kappa^{-1}(\kappa\,s)=s for every s∈D(μ,ν)s\in D(\mu,\nu), so κ−1c\kappa^{-1}c is a lower bound of D(μ,ν)D(\mu,\nu) and hence κ−1c≤inf⁡D(μ,ν)=W2(μ,ν)\kappa^{-1}c\le\inf D(\mu,\nu)=W_{2}(\mu,\nu) by Lower Bound and Greatest Lower Bound; multiplying by the nonnegative κ\kappa (claim 5 again) gives c=κ(κ−1c)≤κ W2(μ,ν)c=\kappa(\kappa^{-1}c)\le\kappa\,W_{2}(\mu,\nu). In both cases ∣u(μ)−u(ν)∣≤κ W2(μ,ν)|u(\mu)-u(\nu)|\le\kappa\,W_{2}(\mu,\nu), so uu is Lipschitz with constant κ\kappa.

Claim 7. Let uu be uniformly continuous and let ε>0\varepsilon>0. By Uniformly Continuous Map Between Metric Spaces there is δ>0\delta>0 such that ∣u(μ)−u(ν)∣<ε|u(\mu)-u(\nu)|<\varepsilon whenever W2(μ,ν)<δW_{2}(\mu,\nu)<\delta. Let X,Y∈L2(Ω;Rd)X,Y\in L^{2}(\Omega;\mathbb{R}^{d}) with ∥X−Y∥L2<δ\lVert X-Y\rVert_{L^{2}}<\delta. Then W2(L(X),L(Y))<δW_{2}(\mathcal{L}(X),\mathcal{L}(Y))<\delta by the domination inequality and claim 2 of Elementary Order Arithmetic in an Ordered Field, hence ∣U(X)−U(Y)∣=∣u(L(X))−u(L(Y))∣<ε|U(X)-U(Y)|=|u(\mathcal{L}(X))-u(\mathcal{L}(Y))|<\varepsilon. So UU is uniformly continuous.

Claim 8. Let (Ω,F,P)(\Omega,\mathcal{F},P) be rich and UU uniformly continuous, and let ε>0\varepsilon>0; choose δ>0\delta>0 with ∣U(X)−U(Y)∣<ε|U(X)-U(Y)|<\varepsilon whenever ∥X−Y∥L2<δ\lVert X-Y\rVert_{L^{2}}<\delta. Let μ,ν∈P2(Rd)\mu,\nu\in\mathcal{P}_{2}(\mathbb{R}^{d}) with W2(μ,ν)<δW_{2}(\mu,\nu)<\delta. Since D(μ,ν)D(\mu,\nu) is nonempty and bounded below with inf⁡D(μ,ν)=W2(μ,ν)<δ\inf D(\mu,\nu)=W_{2}(\mu,\nu)<\delta, claim 2 of Approximation Property of the Supremum and the Infimum in R\mathbb{R} gives s∈D(μ,ν)s\in D(\mu,\nu) with s<δs<\delta, say s=∥X−Y∥L2s=\lVert X-Y\rVert_{L^{2}} with L(X)=μ\mathcal{L}(X)=\mu and L(Y)=ν\mathcal{L}(Y)=\nu. Then ∣u(μ)−u(ν)∣=∣U(X)−U(Y)∣<ε|u(\mu)-u(\nu)|=|U(X)-U(Y)|<\varepsilon. So uu is uniformly continuous.

Claim 9. Let uu be continuous on P2(Rd)\mathcal{P}_{2}(\mathbb{R}^{d}), let X∈L2(Ω;Rd)X\in L^{2}(\Omega;\mathbb{R}^{d}) and let ε>0\varepsilon>0. By Continuous Map Between Metric Spaces applied at L(X)\mathcal{L}(X) there is δ>0\delta>0 such that every ν∈P2(Rd)\nu\in\mathcal{P}_{2}(\mathbb{R}^{d}) with W2(L(X),ν)<δW_{2}(\mathcal{L}(X),\nu)<\delta satisfies ∣u(ν)−u(L(X))∣<ε|u(\nu)-u(\mathcal{L}(X))|<\varepsilon. Let Y∈L2(Ω;Rd)Y\in L^{2}(\Omega;\mathbb{R}^{d}) with ∥X−Y∥L2<δ\lVert X-Y\rVert_{L^{2}}<\delta. Then W2(L(X),L(Y))<δW_{2}(\mathcal{L}(X),\mathcal{L}(Y))<\delta by the domination inequality and claim 2 of Elementary Order Arithmetic in an Ordered Field, so ∣U(Y)−U(X)∣=∣u(L(Y))−u(L(X))∣<ε|U(Y)-U(X)|=|u(\mathcal{L}(Y))-u(\mathcal{L}(X))|<\varepsilon. Hence UU is continuous at XX relative to L2(Ω;Rd)L^{2}(\Omega;\mathbb{R}^{d}), and, XX being arbitrary, continuous on L2(Ω;Rd)L^{2}(\Omega;\mathbb{R}^{d}).

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