Alphabeta Math
TheoremStatement: AI-adaptedProof: AI-adaptedPipeline-generatedjudge pass (gpt-5.6-terra)audited 2026-09-10
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The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.

  • Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
  • AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
  • AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.

These labels describe origin, not correctness: citations and verification chips remain separate evidence.

Taking out what is known

Statement

Assume AC for existence. If X∈L1(P) and Z is bounded real G-measurable, then E[ZX∣G]=ZE[X∣G] almost surely. The identity also holds for finite real G-measurable Z whenever ZX and ZE[X∣G] are integrable. In fact X,ZX∈L1 imply the latter integrability.

Facts & Assumptions

Given: AC, real integrable X, and a real G-measurable factor Z; first assume Z bounded, then assume Z finite and ZX integrable (or explicitly both products integrable).

[F1]

Conditional versions are integrable and satisfy all event integrals. (Conditional expectation as an ae class)

[F2]

Linearity, expectation preservation and the conditional modulus bound hold. (Basic algebra and order properties of conditional expectation)

[F3]

The event identities characterize the version up to almost-sure equality. (Conditional expectation is unique almost surely)

[F4]

Nonnegative measurable functions have increasing nonnegative simple approximations. (Every nonnegative measurable function is the increasing limit of simple measurable functions)

[F5]

Pointwise almost-everywhere convergence with an integrable majorant permits convergence of event integrals. (Dominated convergence)

[F6]

Integrals of increasing nonnegative functions converge to the integral of the limit. (Monotone convergence for the integral)

Proof

technique · direct
1.1F1F2F3

Write U=E[X∣G]. If Z=1B with B∈G, then for every A∈G, ∫AZU=∫A∩BU=∫A∩BX=∫AZX. The products are integrable and ZU is G-measurable, so uniqueness gives the identity. Finite sums of such indicators give the identity for bounded simple Z by linearity.

2.1step 1.1F4F5F3

If ∣Z∣≤M, apply [F4] to Z+ and Z− and subtract their approximations to obtain simple Zn→Z with ∣Zn∣≤M. Then ∣ZnX∣≤M∣X∣ and ∣ZnU∣≤M∣U∣, both integrable majorants. By [F5] in each event identity of step 1.1, ∫AZU=∫AZX. The limit ZU is measurable and integrable, so [F3] proves the bounded case.

3.1step 2.1F2F6

For finite measurable Z with ZX∈L1, set V=E[∣X∣∣G]≥0 and Rn=∣Z∣∧n. The bounded case and expectation preservation imply E[RnV]=E[Rn∣X∣]. MCT gives E[∣Z∣V]=E∣ZX∣<∞. Since ∣U∣≤V almost surely, E∣ZU∣≤E∣ZX∣<∞.

4.1step 2.1step 3.1F5F3

Let Zn=max⁡(−n,min⁡(Z,n)). For each event A the bounded case gives ∫AZnU=∫AZnX. Now ZnU→ZU and ZnX→ZX, dominated by the integrable ∣ZU∣ and ∣ZX∣ respectively. DCT and uniqueness yield E[ZX∣G]=ZU. This proves both the stated two-product extension and its stronger integrability observation.

5.1step 1.1F1∎

The same indicator identity gives locality: if X=Y almost surely on B∈G, then 1BE[X∣G]=E[1BX∣G]=E[1BY∣G]=1BE[Y∣G] as classes. No assertion is made about arbitrary values on exceptional points.

Source notes

Durrett Theorem 4.1.14, printed pp.212–213; locality Theorem 4.1.2, printed p.206. The absolute-product integrability estimate is explicitly proved by ordinary MCT before the signed DCT limit; conditional MCT is not used.

Depends on

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Sources