Alphabeta Math
TheoremStatement: AI-adaptedProof: AI-generatedSession-authored (Fable 5 assisted)precheck passaudited 2026-08-29
How statement and proof provenance work

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.

Tonelli's theorem for nonnegative measurable functions on a sigma-finite product

Statement

Let (X,A,μ) and (Y,B,ν) be sigma-finite measure spaces, and let f:X×Y[0,] be product-measurable. Then xYfxdν and yXfydμ are measurable, and

X×Yfd(μ×ν)=X(Yfxdν)dμ=Y(Xfydμ)dν.

Facts & Assumptions

Given: Sigma-finite measure spaces (X,A,μ) and (Y,B,ν), and a product-measurable function f:X×Y[0,].

[L1]

Sections of a product-measurable function are measurable. (Every section of a product-measurable function is measurable)

[L2]

For a measurable set E, the indicator function satisfies X×Y1Ed(μ×ν)=Xν(Ex)dμ=Yμ(Ey)dν. (For sigma-finite measures, the two section-measure integrals of a measurable set agree)

[L3]

Every nonnegative measurable function admits an increasing sequence of nonnegative simple functions converging pointwise to it. (Every nonnegative measurable function admits an explicit increasing sequence of simple approximations)

[L4]

Monotone convergence passes increasing limits through the integral. (Monotone convergence for the integral)

Proof

technique · direct
1.1

If s is a nonnegative simple function, write s=j=1mcj1Ej with cj0 and measurable sets Ej. Applying [L2] to each indicator 1Ej and summing yields sd(μ×ν)=X(Ysxdν)dμ=Y(Xsydμ)dν. The inner integral functions are measurable because the same is true for each 1Ej and simple combinations preserve measurability.

L2
2.1

Choose simple functions snf by [L3]. Then for each x and y one has (sn)xfx and (sn)yfy, so [L4] gives Y(sn)xdνYfxdν,X(sn)ydμXfydμ. Applying [L4] once more to the equalities of step 1.1 yields the stated measurability and the equality of all three integrals.

L1L3L4step 1.1

Depends on

Used by

Dependency tree · two levels

28 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.

Sources