Proof of The Projection onto One-Particle Tangent Fields: Pairing with Product Fields, Contraction, and Product Fields of Tangent Fields
lemmalem:product-field-projection-properties-wasserstein-2026aThe pairing identity holds on gradients by the definition of the projection and extends to the tangent space by density and the norm identity for product fields; Cauchy-Schwarz with g equal to the projection gives the contraction, and splitting inner products over the particles gives the product-field identity.
Each result cited is universally quantified over the data in its own statement. Write . The spaces and of Wasserstein Spaces, Random Vectors, Vector Fields and Symmetric Matrices in Every Dimension: Standing Notation §fields are real Hilbert spaces, in particular real inner product spaces, so The Cauchy-Schwarz Inequality in a Real Inner Product Space applies in each; their elements are classes of Borel maps, with the operations of The Space of Square-Integrable Random Vectors §classes applied as in that clause. Block maps , configurations and product maps are those of Particle Blocks of the Configuration Space: Block Maps, Configurations, Product Maps and Diagonal Points with , and is the nonnegative square root of Existence and Uniqueness of the Nonnegative Square Root.
Step 1 (Norms and differences of product fields). Let . By Product Fields and the Projection onto One-Particle Tangent Fields §product-field, , and both and are nonnegative, so by the uniqueness in Existence and Uniqueness of the Nonnegative Square Root. Let be Borel representatives of ; then is a Borel representative of by The Space of Square-Integrable Random Vectors §classes. For , the product map of Particle Blocks of the Configuration Space: Block Maps, Configurations, Product Maps and Diagonal Points §product-map and Particle Blocks: Linearity, Splitting of Inner Products, Product Maps and Diagonal Shifts §linear (with ) give
Taking classes, by Product Fields and the Projection onto One-Particle Tangent Fields §product-field and The Space of Square-Integrable Random Vectors §classes; hence .
Step 2 (Pairing against gradients). Let and . Multiplying the identity of Product Fields and the Projection onto One-Particle Tangent Fields §projection by gives . Thus claim 1 holds for every in the set of The Tangent Space of the Wasserstein Space at a Probability Measure §gradients.
Step 3 (Claim 1). Let and , and put and . Let . Since is the closure of in (The Tangent Space of the Wasserstein Space at a Probability Measure §tangent), Characterization of the Closure in a Metric Space by Open Balls (claim 1 implies claim 3) gives with . By Step 2 for , bilinearity of the inner products and Step 1,
so by The Cauchy-Schwarz Inequality in a Real Inner Product Space in both spaces and Step 1, . If , the choice would give (Elementary Order Arithmetic in an Ordered Field, claims 7 and 10), which is impossible. Hence , which is claim 1.
Step 4 (Linearity). Let and , and put . Then , since is a linear subspace 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 §closed, and for every the defining identity of Product Fields and the Projection onto One-Particle Tangent Fields §projection for and and bilinearity give
By the uniqueness in Product Fields and the Projection onto One-Particle Tangent Fields §projection, . So is linear.
Step 5 (Contraction). Let and , so that and, by Step 1, . Claim 1 with and The Cauchy-Schwarz Inequality in a Real Inner Product Space give
If , then . If , then , since would give by claim 10 of Elementary Order Arithmetic in an Ordered Field; hence and, by claim 5 of Elementary Arithmetic in an Ordered Field applied to with the nonnegative factors and , . In both cases , which with Step 4 is claim 2.
Step 6 (Claim 3). Let with Borel representative , and let . The function is Borel by Pairs of Euclidean Points: Coordinate Projections, Pairings, the Product Measure on a Euclidean Space, Borel Norm Functions and Finite Sets §functions and integrable with respect to with , by Square-Integrable Random Vectors: Coordinates, Operations, Almost Sure Equality and the Mean-Square Form §operations on the probability space as in Wasserstein Spaces, Random Vectors, Vector Fields and Symmetric Matrices in Every Dimension: Standing Notation §fields. Since is the measure of Existence and Uniqueness of Tensor Powers, and the Average of the Block Marginals §average (with ) by The One-Particle Marginal of a Probability Measure on the Configuration Space §marginal, that clause shows that each is integrable with respect to and . For , Particle Blocks: Linearity, Splitting of Inner Products, Product Maps and Diagonal Shifts §inner-product (in with ) and Particle Blocks: Linearity, Splitting of Inner Products, Product Maps and Diagonal Shifts §product-map give
Integrating against and using Linearity of the Lebesgue Integral over a Finite Sum of Integrable Functions §linear (all coefficients ),
Thus satisfies for every , and the uniqueness in Product Fields and the Projection onto One-Particle Tangent Fields §projection (with ) gives , which is claim 3.
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Prerequisites
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