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The quadratic Wasserstein distance is a metric

Statement

Assume the Axiom of Choice. For every integer d≥1, the function W2 defined on P2(Rd) is a metric: for all μ,ν,λ∈P2(Rd) it is finite and nonnegative, W2(μ,ν)=0 exactly when μ=ν, W2(μ,ν)=W2(ν,μ), and W2(μ,λ)≤W2(μ,ν)+W2(ν,λ).

Facts & Assumptions

Given: AC and μ,ν,λ∈P2(Rd).

[F2]

Given couplings of μ with ν and ν with λ, under AC there is a joint law of (X,Y,Z) with those two pair marginals. Gluing two Euclidean couplings The Axiom of Choice

[F3]

The scalar L2 Minkowski inequality holds, including finite sums; applied to the nonnegative functions ∣x−y∣ and ∣y−z∣, it combines with the pointwise Euclidean triangle inequality. Minkowski's integral inequality

[F4]

If P is a Borel probability law on a Polish space and F is Borel into a Polish space, define F#P(B)=P(F−1(B)); preimages make this a Borel probability law, coordinate marginals compose with coordinate maps, and ∫h d(F#P)=∫h(F) dP for nonnegative Borel h by change of variables for expectation. Borel probability law on a polish space Measures on sigma-algebras Change of variables for expectation

Proof

1.1givenF1F4

The product coupling has finite cost by [F1], so W2 is finite and nonnegative. The diagonal map Δ(x)=(x,x) is Borel, and its pushforward Δ#μ is a Borel probability by [F4]. Its two coordinate marginals are (pr⁡i∘Δ)#μ=μ, and its cost is ∫∣Δ(x)1−Δ(x)2∣2dμ(x)=0 by [F4], hence W2(μ,μ)=0. The coordinate swap S(x,y)=(y,x) is Borel; for every coupling π of μ,ν, [F4] shows S#π is a probability with first marginal ν and second marginal μ, while its cost is ∫∣S(x,y)1−S(x,y)2∣2dπ=∫∣x−y∣2dπ by [F4]. Since S is its own inverse, this correspondence is onto and preserves costs, proving equality of the two infima.

2.1givenF1step 1.1

If W2(μ,ν)=0, choose an optimal coupling π using [F1]. Its integral of ∣x−y∣2 is zero. For each positive integer k, the set {∣x−y∣≥1/k} has π-measure zero, since its contribution to the integral is at least k−2 times its measure. Their union is the complement of the diagonal, so π is concentrated on the diagonal. For every Borel set A, both coordinate indicators agree π-almost everywhere, giving μ(A)=π(A×Rd)=π(Rd×A)=ν(A). Conversely, if μ=ν, step 1.1 gives distance zero.

3.1givenF1F2F3F4step 1.1step 2.1∎

Choose optimal couplings π12 of (μ,ν) and π23 of (ν,λ) using [F1]. Glue them by [F2] to obtain a Borel probability γ on R3d. The Borel projection Q(x,y,z)=(x,z) has pushforward Q#γ a Borel probability by [F4]; its coordinate marginals are μ and λ, so it is a coupling. By [F4] its cost is ∫∣u−v∣2d(Q#γ)(u,v)=∫∣x−z∣2dγ(x,y,z). Pointwise, ∣x−z∣≤∣x−y∣+∣y−z∣; applying [F3] on (R3d,γ) gives W2(μ,λ)≤(∫∣x−z∣2dγ)1/2≤W2(μ,ν)+W2(ν,λ). This proves the triangle inequality and all metric axioms.

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