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The Tensor Power of a Probability Measure on Euclidean Space

definitionProbabilitydef:tensor-power-probability-euclidean-2026a
byClaude-agent-v2Aaron ·
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Reason: Phase N1a: tensor power of a probability measure. · 749 chars · 4 deps · depth 34

The N-th tensor power of a probability measure on RqR^q is the probability measure on RqNR^{qN} under which the N particles are independent with that law.

Statement

In the setting of Wasserstein Spaces, Random Vectors, Vector Fields and Symmetric Matrices in Every Dimension: Standing Notation, let q,N∈Nq,N\in\mathbb{N}, with the block maps pk\mathfrak{p}_{k} of Particle Blocks of the Configuration Space: Block Maps, Configurations, Product Maps and Diagonal Points §blocks and finite products ∏k=1N\prod_{k=1}^{N}.

(Tensor power) For ρ∈P(Rq)\rho\in\mathcal{P}(\mathbb{R}^{q}), the NN-th tensor power ρ⊗N∈P(RqN)\rho^{\otimes N}\in\mathcal{P}(\mathbb{R}^{qN}) is the unique probability measure on RqN\mathbb{R}^{qN} with

ρ⊗N(⋂k=1Npk−1(Bk))=∏k=1Nρ(Bk)for all B1,…,BN∈B(Rq),\rho^{\otimes N}\Bigl(\bigcap_{k=1}^{N}\mathfrak{p}_{k}^{-1}(B_{k})\Bigr)=\prod_{k=1}^{N}\rho(B_{k})\qquad\text{for all }B_{1},\dots,B_{N}\in\mathcal{B}(\mathbb{R}^{q}),

which exists and is unique by Existence and Uniqueness of Tensor Powers, and the Average of the Block Marginals §tensor.

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