TheoremBase

Head Maps of a Noise-Optimal Coupling: the Head of the Target is a Function of the Source

For a noise-optimal coupling out of a measure with a density relative to a diagonal Gaussian measure, the first n coordinates of the target are almost surely a Borel function of the source.

Statement

In the setting of Probability Measures on a Hilbert Space Transported in the Noise Norm: Standing Notation, with the maps pnp_{n} of Borel Probability Measures on a Real Hilbert Space with an Orthonormal Basis: Standing Notation §coordinates, which are Borel by Borel Sets of a Hilbert Space with an Orthonormal Basis: Coordinates, Determination by Finite-Dimensional Projections, and Pairs §continuity, let cc be a variance sequence with diagonal Gaussian measure γc\gamma_{c}, and let μ,ν\mu,\nu belong to the set Pρa\mathcal{P}^{a}_{\rho} of The Measures Noise-Connected to the Reference Measure §space, so that the ordered pair (μ,ν)(\mu,\nu) is noise-connected by The Noise Wasserstein Distance is a Metric on the Measures Noise-Connected to the Reference Measure: Existence of Noise-Optimal Couplings, Comparison with the Quadratic Wasserstein Distance and Lower Semicontinuity §connected. Suppose that μ\mu has a density with respect to γc\gamma_{c}, and let π\pi be a noise-optimal coupling of μ\mu and ν\nu. Let n∈Nn\in\mathbb{N}, write id\mathrm{id} for the identity map of XX, and let X×RnX\times\mathbb{R}^{n} carry the product σ\sigma-algebra B(X)⊗B(Rn)\mathcal{B}(X)\otimes\mathcal{B}(\mathbb{R}^{n}). The components π1\pi_{1} and pn∘π2p_{n}\circ\pi_{2} of the map (π1,pn∘π2):X×X→X×Rn(\pi_{1},p_{n}\circ\pi_{2}):X\times X\to X\times\mathbb{R}^{n} are Borel by Borel Sets of a Hilbert Space with an Orthonormal Basis: Coordinates, Determination by Finite-Dimensional Projections, and Pairs §product-sigma and claim 4 of Borel Measurability and Bounded Integration on a Metric Space. By Pairings into a Product, the Graph of a Measurable Map, and Couplings Concentrated on a Graph §pairing, applied with (X,B(X))(X,\mathcal{B}(X)) and Rn\mathbb{R}^{n} in place of (Y,Y)(Y,\mathcal{Y}) and ZZ, this map and the map (id,S)(\mathrm{id},S) for every Borel S:X→RnS:X\to\mathbb{R}^{n} are measurable into X×RnX\times\mathbb{R}^{n}; image measures are those of claim 1 of Image Measures, Measures with Densities, and Change of Variables.

1. (The head of the target is a function of the source) There is a Borel map Tn:X→RnT_{n}:X\to\mathbb{R}^{n} with

(π1,pn∘π2)#π=(id,Tn)#μ.(\pi_{1},p_{n}\circ\pi_{2})_{\#}\pi=(\mathrm{id},T_{n})_{\#}\mu .

2. (Almost sure form) Let TnT_{n} be as in claim 1. The set Gn={z∈X×X: pn(y)=Tn(x)}G_{n}=\{z\in X\times X:\ p_{n}(y)=T_{n}(x)\}, where x=π1(z)x=\pi_{1}(z) and y=π2(z)y=\pi_{2}(z), is the preimage under (π1,pn∘π2)(\pi_{1},p_{n}\circ\pi_{2}) of the graph of TnT_{n}, which belongs to B(X)⊗B(Rn)\mathcal{B}(X)\otimes\mathcal{B}(\mathbb{R}^{n}) by Pairings into a Product, the Graph of a Measurable Map, and Couplings Concentrated on a Graph §graph-measurable, Rn\mathbb{R}^{n} being separable by Euclidean Space is a Separable Metric Space §separable; so Gn∈B(X×X)G_{n}\in\mathcal{B}(X\times X), and π(Gn)=1\pi(G_{n})=1.

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