TheoremBase

For the squared distance, differentiability along couplings is the published expansion at a uniquely mapped source, continuity of the gradient is the source stability of the optimal displacement, and the translation identity makes the translated function a quadratic. For a function of the mean, the displacement pairing of a constant field is a pairing with the difference of the means, which is controlled by the Wasserstein distance, so everything reduces to the calculus of the function on Euclidean space.

Proof

Each result cited is universally quantified over the data in its own statement. For z∈Rd+dz\in\mathbb{R}^{d+d} we write x=pr1(z)x=\mathrm{pr}_{1}(z) and y=pr2(z)y=\mathrm{pr}_{2}(z), as in The Intrinsic Calculus on the Wasserstein Space: Standing Notation (i). Two facts about means are used throughout, both from The Mean of a Square-Integrable Probability Measure, Its Lift, Its Centring, and Functions of the Mean and Centred Integrals as Test Functions (i): ∥m(μ)−m(ν)∥≤W2(μ,ν)\lVert m(\mu)-m(\nu)\rVert\le W_{2}(\mu,\nu), and m((τa)#μ)=m(μ)+am((\tau_{a})_{\#}\mu)=m(\mu)+a. Also W2(μ,ν)≤I(π)W_{2}(\mu,\nu)\le\sqrt{I(\pi)} for every π∈Π(μ,ν)\pi\in\Pi(\mu,\nu), by The Quadratic Wasserstein Distance on Euclidean Space (i) and claim 2 of Monotonicity of Squaring on the Nonnegative Elements of an Ordered Field.

Claim 1. Let μ∈Q\mu\in Q. By The Map Property of a Set of Probability Measures (i) the pair (μ,ν0)(\mu,\nu_{0}) is uniquely mapped, so an optimal map SμS_{\mu} from μ\mu to ν0\nu_{0} exists, its class does not depend on the choice by The Optimal Map as a Square-Integrable Vector Field: Integrability, Transport Cost and Uniqueness of the Class (iii), and id−Sμ∈Tμ\mathrm{id}-S_{\mu}\in T_{\mu}. We verify the four properties of Intrinsic Test Functions on the Wasserstein Space and Their Translation Hessians (i).

(a) For μ,μ′∈P2(Rd)\mu,\mu'\in\mathcal{P}_{2}(\mathbb{R}^{d}) the triangle inequality and the symmetry of W2W_{2} (The Quadratic Wasserstein Distance is a Metric on the Wasserstein Space (iii), The Quadratic Wasserstein Distance is a Metric on the Wasserstein Space (i)) give W2(μ,ν0)≤W2(μ,μ′)+W2(μ′,ν0)W_{2}(\mu,\nu_{0})\le W_{2}(\mu,\mu')+W_{2}(\mu',\nu_{0}) and the same with μ\mu and μ′\mu' exchanged, so ∣W2(μ,ν0)−W2(μ′,ν0)∣≤W2(μ,μ′)|W_{2}(\mu,\nu_{0})-W_{2}(\mu',\nu_{0})|\le W_{2}(\mu,\mu') by claim 6 of Properties of the Absolute Value in an Ordered Field. Hence the map μ↦W2(μ,ν0)\mu\mapsto W_{2}(\mu,\nu_{0}) is continuous on P2(Rd)\mathcal{P}_{2}(\mathbb{R}^{d}), the radius ε\varepsilon serving for the accuracy ε\varepsilon, and ψ\psi, its product with itself, is continuous by claim 5 of Continuity of Sums and Products of Real-Valued Functions on a Metric Space.

(b) By The Squared Wasserstein Distance to a Fixed Measure: a One-Sided Bound Along Couplings, Differentiability at a Uniquely Mapped Source, and the Translation and Centring Identities (ii), ψ\psi is differentiable along couplings at μ\mu with gradient 2(id−Sμ)2(\mathrm{id}-S_{\mu}), which lies in TμT_{\mu} because id−Sμ\mathrm{id}-S_{\mu} does and TμT_{\mu} is a linear subspace of L2(μ;Rd)L^{2}(\mu;\mathbb{R}^{d}) by Basic Properties of the Tangent Space: Closed Subspace, the Identity Map Belongs to It, Second-Moment Limits, and Representation of Bounded Functionals on Gradients (i). By Differentiability of a Function on the Wasserstein Space Along Couplings, and Its Gradient (ii), ∇ψ(μ)=2(id−Sμ)\nabla\psi(\mu)=2(\mathrm{id}-S_{\mu}).

(c) Let (μn)n∈N(\mu_{n})_{n\in\mathbb{N}} be a sequence in QQ and let πn∈Π(μn,μ)\pi_{n}\in\Pi(\mu_{n},\mu) with I(πn)→0I(\pi_{n})\to0. For each nn let TnT_{n} be an optimal map from μn\mu_{n} to ν0\nu_{0}, which exists as above since μn∈Q\mu_{n}\in Q; by (b), ∇ψ(μn)=2(id−Tn)\nabla\psi(\mu_{n})=2(\mathrm{id}-T_{n}). By Square-Integrable Random Vectors: Coordinates, Operations, Almost Sure Equality and the Mean-Square Form (v) these gradients are represented by x↦2(x−Tn(x))x\mapsto2(x-T_{n}(x)) and y↦2(y−Sμ(y))y\mapsto2(y-S_{\mu}(y)), and for every zz,

∥2(x−Tn(x))−2(y−Sμ(y))∥2=4 ∥(x−Tn(x))−(y−Sμ(y))∥2,\bigl\lVert2\bigl(x-T_{n}(x)\bigr)-2\bigl(y-S_{\mu}(y)\bigr)\bigr\rVert^{2}=4\,\bigl\lVert\bigl(x-T_{n}(x)\bigr)-\bigl(y-S_{\mu}(y)\bigr)\bigr\rVert^{2},

by the vector arithmetic of Rd\mathbb{R}^{d} and claim 5 of Properties of the Euclidean Norm on Rn\mathbb{R}^n: Square, Distance, Vanishing, Coordinate Bounds, Homogeneity, Triangle Inequalities and Expansion of a Square, the absolute value of the positive number 22 (claim 8 of Elementary Order Arithmetic in an Ordered Field) being 22 by Absolute Value in an Ordered Field. By claim 1 of Linearity and Monotonicity of the Lebesgue Integral, and the Integrability Criterion the discrepancy of ∇ψ(μn)\nabla\psi(\mu_{n}) and ∇ψ(μ)\nabla\psi(\mu) along πn\pi_{n} is 44 times the discrepancy of id−Tn\mathrm{id}-T_{n} and id−Sμ\mathrm{id}-S_{\mu} along πn\pi_{n}, which converges to 00 by Stability of the Optimal Displacement Under Perturbation of the Source Along Couplings of Vanishing Cost (ii), read with ν0\nu_{0}, μ\mu, SμS_{\mu} in place of its TT, (μn)(\mu_{n}), (Tn)(T_{n}) and (πn)(\pi_{n}); so the former converges to 00 by claim 3 of Arithmetic of Limits of Real Sequences.

(d) Let ρ∈P2(Rd)\rho\in\mathcal{P}_{2}(\mathbb{R}^{d}) and a∈Rda\in\mathbb{R}^{d}. The translation τ0Rd\tau_{0_{\mathbb{R}^{d}}} is the identity map, so (τ0Rd)#ν0=ν0(\tau_{0_{\mathbb{R}^{d}}})_{\#}\nu_{0}=\nu_{0} by the definition of the push-forward in Probability Measures on Euclidean Space and Random Vectors: Standing Notation (iv), and The Squared Wasserstein Distance to a Fixed Measure: a One-Sided Bound Along Couplings, Differentiability at a Uniquely Mapped Source, and the Translation and Centring Identities (iii), read with ρ\rho, ν0\nu_{0}, aa and b=0Rdb=0_{\mathbb{R}^{d}}, gives

ψ((τa)#ρ)=W2(ρ,ν0)2+2 a⋅(m(ρ)−m(ν0))+∥a∥2.\psi\bigl((\tau_{a})_{\#}\rho\bigr)=W_{2}(\rho,\nu_{0})^{2}+2\,a\cdot\bigl(m(\rho)-m(\nu_{0})\bigr)+\lVert a\rVert^{2}.

Since ∥a∥2=a⋅a\lVert a\rVert^{2}=a\cdot a by claim 1 of Properties of the Euclidean Norm on Rn\mathbb{R}^n: Square, Distance, Vanishing, Coordinate Bounds, Homogeneity, Triangle Inequalities and Expansion of a Square, a⋅a=a⋅(Ida)a\cdot a=a\cdot(I_{d}a) by claim 2 of Linearity of the Matrix-Vector Product and the Quadratic Form as a Double Sum, and (2Id)a=2(Ida)(2I_{d})a=2(I_{d}a) by claim 1 of that lemma, the right-hand side is 12 a⋅((2Id)a)+q⋅a+c\tfrac{1}{2}\,a\cdot\bigl((2I_{d})a\bigr)+q\cdot a+c with q=2(m(ρ)−m(ν0))q=2(m(\rho)-m(\nu_{0})) and c=W2(ρ,ν0)2c=W_{2}(\rho,\nu_{0})^{2}, using 2 a⋅(m(ρ)−m(ν0))=q⋅a2\,a\cdot(m(\rho)-m(\nu_{0}))=q\cdot a by claims 1 and 4 of The Dot Product on Rn\mathbb{R}^n Is Symmetric, Bilinear and Positive Definite. The matrix 2Id2I_{d} is symmetric, its entries being unchanged when the indices are interchanged. By Quadratic and Affine Functions of Class C2C^2, Translation, and Quadratic Perturbation of Semiconvexity (i), read in dimension dd with M=2IdM=2I_{d}, the function a↦ψ((τa)#ρ)a\mapsto\psi((\tau_{a})_{\#}\rho) is of class C2C^{2} on Rd\mathbb{R}^{d} with Hessian matrix 2Id2I_{d} at every point; so property (d) holds, and Hψ(ρ)=2IdH_{\psi}(\rho)=2I_{d} by Intrinsic Test Functions on the Wasserstein Space and Their Translation Hessians (ii).

Claim 2. A first-order bound for ϕ\phi. Let a∈Rda\in\mathbb{R}^{d} and let ε∈R\varepsilon\in\mathbb{R} be positive. We show that there is a positive r∈Rr\in\mathbb{R} with

∣ϕ(b)−ϕ(a)−Dϕ(a)⋅(b−a)∣≤ε ∥b−a∥whenever ∥b−a∥<r.(†)\bigl|\phi(b)-\phi(a)-D\phi(a)\cdot(b-a)\bigr|\le\varepsilon\,\lVert b-a\rVert\qquad\text{whenever }\lVert b-a\rVert<r. \tag{$\dagger$}

Let g:Rd→Rg:\mathbb{R}^{d}\to\mathbb{R} be g(b)=ϕ(b)−Dϕ(a)⋅bg(b)=\phi(b)-D\phi(a)\cdot b. By Quadratic and Affine Functions of Class C2C^2, Translation, and Quadratic Perturbation of Semiconvexity (i), read with M=0dM=0_{d}, q=−Dϕ(a)q=-D\phi(a) and c=0c=0, the map b↦−Dϕ(a)⋅bb\mapsto-D\phi(a)\cdot b is of class C2C^{2} with constant gradient −Dϕ(a)-D\phi(a), so gg is of class C2C^{2} on Rd\mathbb{R}^{d} by claim 3 of Constants, Affine Functions, Sums, Products and Quotients of Cᵏ Functions, with ∂ig(b)=∂iϕ(b)−∂iϕ(a)\partial_{i}g(b)=\partial_{i}\phi(b)-\partial_{i}\phi(a) by claim 1 of that lemma. Put ε1=ε (d+1)−1\varepsilon_{1}=\varepsilon\,(\sqrt{d}+1)^{-1}, positive. By Continuity of the Value, Gradient and Hessian Maps of a Differentiable Function (ii), read in dimension dd with V=RdV=\mathbb{R}^{d}, the gradient map of ϕ\phi is continuous at aa, so there is a positive rr with ∥Dϕ(b′)−Dϕ(a)∥<ε1\lVert D\phi(b')-D\phi(a)\rVert<\varepsilon_{1} whenever ∥b′−a∥<r\lVert b'-a\rVert<r; for such b′b' and each i∈[d]i\in[d], ∣∂ig(b′)∣≤∥Dϕ(b′)−Dϕ(a)∥<ε1|\partial_{i}g(b')|\le\lVert D\phi(b')-D\phi(a)\rVert<\varepsilon_{1} by claim 4 of Properties of the Euclidean Norm on Rn\mathbb{R}^n: Square, Distance, Vanishing, Coordinate Bounds, Homogeneity, Triangle Inequalities and Expansion of a Square. Let bb satisfy ∥b−a∥<r\lVert b-a\rVert<r. Every point a+τ(b−a)a+\tau(b-a) with τ∈[0,1]\tau\in[0,1] satisfies ∥τ(b−a)∥=τ∥b−a∥≤∥b−a∥<r\lVert\tau(b-a)\rVert=\tau\lVert b-a\rVert\le\lVert b-a\rVert<r by claim 5 of Properties of the Euclidean Norm on Rn\mathbb{R}^n: Square, Distance, Vanishing, Coordinate Bounds, Homogeneity, Triangle Inequalities and Expansion of a Square, so claim (i) of Multivariate Taylor Expansion with Uniform Second-Order Remainder, read with W=RdW=\mathbb{R}^{d}, f=gf=g and M1=ε1M_{1}=\varepsilon_{1}, gives ∣g(b)−g(a)∣≤d ε1∥b−a∥≤ε∥b−a∥|g(b)-g(a)|\le\sqrt{d}\,\varepsilon_{1}\lVert b-a\rVert\le\varepsilon\lVert b-a\rVert. As g(b)−g(a)=ϕ(b)−ϕ(a)−Dϕ(a)⋅(b−a)g(b)-g(a)=\phi(b)-\phi(a)-D\phi(a)\cdot(b-a) by the second identity of claim 5 of The Dot Product on Rn\mathbb{R}^n Is Symmetric, Bilinear and Positive Definite, this is (†)(\dagger).

We now verify the four properties of Intrinsic Test Functions on the Wasserstein Space and Their Translation Hessians (i) for χ\chi on QQ.

(a) Let μ∈P2(Rd)\mu\in\mathcal{P}_{2}(\mathbb{R}^{d}) and let ε∈R\varepsilon\in\mathbb{R} be positive. By Continuity of the Value, Gradient and Hessian Maps of a Differentiable Function (i) there is a positive rr with ∣ϕ(b)−ϕ(m(μ))∣<ε|\phi(b)-\phi(m(\mu))|<\varepsilon whenever ∥b−m(μ)∥<r\lVert b-m(\mu)\rVert<r. If W2(μ′,μ)<rW_{2}(\mu',\mu)<r, then ∥m(μ′)−m(μ)∥<r\lVert m(\mu')-m(\mu)\rVert<r, so ∣χ(μ′)−χ(μ)∣<ε|\chi(\mu')-\chi(\mu)|<\varepsilon. Thus χ\chi is continuous.

(b) Let μ∈Q\mu\in Q, put a=m(μ)a=m(\mu), and let η\eta be the class of the constant map with value Dϕ(a)D\phi(a); then η∈Tμ\eta\in T_{\mu} by Gradients of Functions with Bounded Derivatives Belong to the Tangent Space; Constants Are Tangent; the Score Identity; the Score Has Mean Zero; Translation of Tangent Fields (ii). Let ε∈R\varepsilon\in\mathbb{R} be positive and let rr be as in (†)(\dagger); put θ=r\theta=r. Let ν∈P2(Rd)\nu\in\mathcal{P}_{2}(\mathbb{R}^{d}) and π∈Π(μ,ν)\pi\in\Pi(\mu,\nu) satisfy I(π)<θ2I(\pi)<\theta^{2}, so that I(π)<θ\sqrt{I(\pi)}<\theta by claim 1 of Monotonicity of Squaring on the Nonnegative Elements of an Ordered Field. By The Displacement Pairing of a Square-Integrable Vector Field Along a Coupling (v), J(η,π)=Dϕ(a)⋅(m(ν)−m(μ))\mathcal{J}(\eta,\pi)=D\phi(a)\cdot(m(\nu)-m(\mu)), and ∥m(ν)−m(μ)∥≤W2(μ,ν)≤I(π)<r\lVert m(\nu)-m(\mu)\rVert\le W_{2}(\mu,\nu)\le\sqrt{I(\pi)}<r. So (†)(\dagger) with b=m(ν)b=m(\nu) gives

∣χ(ν)−χ(μ)−J(η,π)∣≤ε ∥m(ν)−m(μ)∥≤εI(π),\bigl|\chi(\nu)-\chi(\mu)-\mathcal{J}(\eta,\pi)\bigr|\le\varepsilon\,\lVert m(\nu)-m(\mu)\rVert\le\varepsilon\sqrt{I(\pi)},

the last step by claim 5 of Elementary Arithmetic in an Ordered Field. Hence χ\chi is differentiable along couplings at μ\mu with gradient η\eta, and ∇χ(μ)=η\nabla\chi(\mu)=\eta by Differentiability of a Function on the Wasserstein Space Along Couplings, and Its Gradient (ii).

(c) Let μ∈Q\mu\in Q, let (μn)n∈N(\mu_{n})_{n\in\mathbb{N}} be a sequence in QQ, and let πn∈Π(μn,μ)\pi_{n}\in\Pi(\mu_{n},\mu) with I(πn)→0I(\pi_{n})\to0. Put cn=Dϕ(m(μn))c_{n}=D\phi(m(\mu_{n})) and c=Dϕ(m(μ))c=D\phi(m(\mu)). By (b) the discrepancy of ∇χ(μn)\nabla\chi(\mu_{n}) and ∇χ(μ)\nabla\chi(\mu) along πn\pi_{n} is the integral against the probability measure πn\pi_{n} of the constant ∥cn−c∥2\lVert c_{n}-c\rVert^{2}, which is ∥cn−c∥2\lVert c_{n}-c\rVert^{2} by The Integral of an Indicator Function is the Measure of the Set and claim 1 of Linearity and Monotonicity of the Lebesgue Integral, and the Integrability Criterion. Let ε∈R\varepsilon\in\mathbb{R} be positive and let ε1\varepsilon_{1} be the lesser of ε\varepsilon and 11, positive by claim 9 of Elementary Order Arithmetic in an Ordered Field. By Continuity of the Value, Gradient and Hessian Maps of a Differentiable Function (ii) there is a positive rr with ∥Dϕ(b)−c∥<ε1\lVert D\phi(b)-c\rVert<\varepsilon_{1} whenever ∥b−m(μ)∥<r\lVert b-m(\mu)\rVert<r. Since I(πn)→0I(\pi_{n})\to0 there is N∈NN\in\mathbb{N} with I(πn)<r2I(\pi_{n})<r^{2} for n≥Nn\ge N, and then ∥m(μn)−m(μ)∥≤W2(μn,μ)≤I(πn)<r\lVert m(\mu_{n})-m(\mu)\rVert\le W_{2}(\mu_{n},\mu)\le\sqrt{I(\pi_{n})}<r, so ∥cn−c∥<ε1\lVert c_{n}-c\rVert<\varepsilon_{1} and ∥cn−c∥2<ε1ε1≤ε1≤ε\lVert c_{n}-c\rVert^{2}<\varepsilon_{1}\varepsilon_{1}\le\varepsilon_{1}\le\varepsilon, by claims 10 and 2 of Elementary Order Arithmetic in an Ordered Field and claim 5 of Elementary Arithmetic in an Ordered Field. So the discrepancies converge to 00.

(d) Let ρ∈P2(Rd)\rho\in\mathcal{P}_{2}(\mathbb{R}^{d}). For a∈Rda\in\mathbb{R}^{d}, χ((τa)#ρ)=ϕ(m(ρ)+a)=ϕ(a+m(ρ))\chi((\tau_{a})_{\#}\rho)=\phi(m(\rho)+a)=\phi(a+m(\rho)). By Quadratic and Affine Functions of Class C2C^2, Translation, and Quadratic Perturbation of Semiconvexity (ii), read with V=RdV=\mathbb{R}^{d} and b=m(ρ)b=m(\rho), for which V−b=RdV-b=\mathbb{R}^{d}, this function of aa is of class C2C^{2} on Rd\mathbb{R}^{d} with Hessian matrix D2ϕ(a+m(ρ))D^{2}\phi(a+m(\rho)) at aa; at a=0Rda=0_{\mathbb{R}^{d}} it is D2ϕ(m(ρ))D^{2}\phi(m(\rho)). So property (d) holds and Hχ(ρ)=D2ϕ(m(ρ))H_{\chi}(\rho)=D^{2}\phi(m(\rho)) by Intrinsic Test Functions on the Wasserstein Space and Their Translation Hessians (ii).

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