Existence of a Markov category of measurable spaces with conditional expectations

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A Markov category has objects given by measurable spaces (X,ΣX)(X,\Sigma_X), or variants such as measure algebras, and morphisms (X,ΣX)→(Y,ΣY)(X,\Sigma_X) \to (Y,\Sigma_Y) given by suitable positive unital linear maps

L∞(Y,ΣY)⟶L∞(X,ΣX),\mathcal{L}^\infty(Y,\Sigma_Y) \longrightarrow \mathcal{L}^\infty(X,\Sigma_X),

that preserve bounded directed suprema. Its monoidal structure is a suitable variant of the product of measurable spaces, and the comultiplication maps are induced by restriction to the diagonal

L∞(X×X,ΣX⊗ΣX)⟶L∞(X,ΣX).\mathcal{L}^\infty(X\times X,\Sigma_X \otimes \Sigma_X) \longrightarrow \mathcal{L}^\infty(X,\Sigma_X).

Conditional-expectation Markov category conjecture. Such a Markov category exists, with conditionals in the sense of the paper's definition, and these conditionals are given by conditional expectations. This would provide a categorical framework for conditional expectations in measure-theoretic probability. The precise choice of measurable-space variants, morphisms, and product structure remains to be established.

References

Primary source

Tobias Fritz, “A synthetic approach to Markov kernels, conditional independence and theorems on sufficient statistics”, arXiv:1908.07021 (2020).

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