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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.

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✓ 23 results · all verified · 9 also independently AI-judged
Every result on this page is machine-checked by a proof checker and read in full and owner-audited; the judge is an additional, independent cross-model AI review of the proofs. The 14 not AI-judged were verified by owner audit (typically over a confirmed judge false positive), not failures.

Product Measures and the Fubini Tonelli Theorems

1 · Prerequisites

2 · Summary

This page fixes the sigma-finite product-measure route used throughout the rest of the measure-theory track: sections, the measurable-set and functional forms of Tonelli and Fubini, the completed-product weakening, the Euclidean product identifications, and the geometric payoffs that later pages reuse.

The false statements isolate the exact hypotheses that do real work: sigma-finiteness for uniqueness and Tonelli, absolute integrability for Fubini, completion for pointwise section measurability, and second countability for the Euclidean Borel-product identification.

3 · Logical flowchart

4 · Definitions, theorems and proofs

DefinitionDefinition: AI-adaptedProof: Not applicablejudge pass (gpt-5.6-terra)audited 2026-08-29Open item page →

Measurable rectangles in a product of measurable spaces

Definition

Let (X,A) and (Y,B) be measurable spaces. A subset of X×Y is a measurable rectangle if it has the form A×B with A∈A and B∈B.

The ambient sigma-algebras matter: the same set may be a measurable rectangle for one pair (A,B) and not for another.

DefinitionDefinition: AI-adaptedProof: Not applicablejudge pass (gpt-5.6-terra)audited 2026-08-29Open item page →

The product sigma-algebra and its finite iterates

Definition

Let (X,A) and (Y,B) be measurable spaces. Their product sigma-algebra is

A⊗B:=σ({A×B:A∈A, B∈B}),

the sigma-algebra on X×Y generated by the measurable rectangles of Measurable rectangles in a product of measurable spaces.

For the empty family, put ∏i<0Xi:={()} and define its empty product sigma-algebra by

⨂i<0Ai:={∅,{()}}.

For a nonempty finite family of measurable spaces (Xi,Ai) with i<n, the finite product sigma-algebra is defined recursively by

⨂i<1Ai:=A0,⨂i<n+1Ai:=(⨂i<nAi)⊗An.

This recursive definition is the finite base case used later when the library passes to countable product constructions.

LemmaStatement: AI-adaptedProof: AI-generatedprecheck passjudge pass (gpt-5.6-terra)audited 2026-08-29Open item page →

Finite disjoint unions of measurable rectangles form an algebra generating the product sigma-algebra

Statement

Let (X,A) and (Y,B) be measurable spaces. The family of finite disjoint unions of measurable rectangles in X×Y is an algebra of subsets of X×Y, and it generates A⊗B.

Facts & Assumptions

Given: Measurable spaces (X,A) and (Y,B).

[L1]

A measurable rectangle has the form A×B with A∈A and B∈B. (Measurable rectangles in a product of measurable spaces)

[L2]

The product sigma-algebra A⊗B is the sigma-algebra generated by the measurable rectangles. (The product sigma-algebra and its finite iterates)

[A1]

For rectangles, (A1×B1)∩(A2×B2)=(A1∩A2)×(B1∩B2), and (X×Y)∖(A×B)=(Ac×Y)∪(A×Bc).

[A2]

If Rj=Aj×Bj for 1≤j≤n, take the nonempty Boolean atoms generated by A1,…,An in X and by B1,…,Bn in Y. The products of an X-atom and a Y-atom are finitely many pairwise disjoint measurable rectangles partitioning X×Y, and each Rj, hence also ⋃j=1nRj, is the union of a subfamily of these product atoms.

Proof

technique · direct
1.1L1A1

By [L1] and [A1], the intersection of two measurable rectangles is again a measurable rectangle, and the complement of a measurable rectangle is a finite union of measurable rectangles.

2.1step 1.1A2

Let R be the family of finite disjoint unions of measurable rectangles. It contains ∅ and X×Y. If E,F∈R, then [A2] disjointifies the finite union E∪F into finitely many pairwise disjoint measurable rectangles, so E∪F∈R. Likewise E∖F=E∩Fc belongs to R by step 1.1. Thus R is an algebra.

3.1L2step 2.1∎

Every measurable rectangle belongs to R, so [L2] gives A⊗B=σ(measurable rectangles)⊆σ(R). The reverse inclusion holds because every member of R is a finite union of measurable rectangles and hence lies in A⊗B. Therefore σ(R)=A⊗B, and R is an algebra generating the product sigma-algebra.

RemarkRemark: AI-adaptedProof: Not applicableaudited 2026-08-29Open item page →

The product measure can also be constructed from the rectangle algebra by Caratheodory extension

Assume the Axiom of Countable Choice (The Axiom of Countable Choice (ACω)). The page's main theorem chain defines the sigma-finite product measure through sections and iterated integrals. There is a second standard construction. Its additional input is the separate verification, carried out in the references above, that the rectangle rule λ0(A×B):=μ(A)ν(B) extends consistently to a premeasure on the algebra of Finite disjoint unions of measurable rectangles form an algebra generating the product sigma-algebra. Once that premeasure has been established, Assuming countable choice, a premeasure extends through its induced outer measure extends it to the generated product sigma-algebra; the extension theorem does not itself supply the premeasure verification.

When the rectangle premeasure is sigma-finite, Assuming countable choice, the Carathéodory domain is the completion of the sigma-finite extension identifies the full Caratheodory domain with the completion of that generated extension. Uniqueness of the product measure itself is supplied separately by the main product-measure theorem later on this page, not by either cited Caratheodory result.

DefinitionDefinition: AI-adaptedProof: Not applicablejudge pass (gpt-5.6-terra)audited 2026-08-29Open item page →

Sections E_x, E^y, f_x, and f^y on a product

Definition

Let E⊆X×Y. For x∈X and y∈Y, the horizontal and vertical sections of E are

Ex:={y∈Y:(x,y)∈E},Ey:={x∈X:(x,y)∈E}.

If f:X×Y→Z is a function, its sections are

fx:Y→Z,fx(y):=f(x,y),fy:X→Z,fy(x):=f(x,y).

The notation remembers which variable has been frozen: the subscript freezes x, while the superscript freezes y.

TheoremStatement: AI-adaptedProof: AI-generatedprecheck passjudge pass (gpt-5.6-terra)audited 2026-08-29Open item page →

Every section of a product-measurable set is measurable

Statement

Let (X,A) and (Y,B) be measurable spaces. If E∈A⊗B, then Ex∈B for every x∈X and Ey∈A for every y∈Y.

Facts & Assumptions

Given: Measurable spaces (X,A) and (Y,B), and a set E∈A⊗B.

[L1]

The product sigma-algebra A⊗B is generated by the measurable rectangles. (The product sigma-algebra and its finite iterates)

[L2]

The generated sigma-algebra is the smallest sigma-algebra containing the generating family. (Nonempty intersections of sigma-algebras are sigma-algebras, so the generated sigma-algebra exists and is minimal)

[A1]

For fixed x∈X, (A×B)x={B,x∈A,∅,x∉A, and for fixed y∈Y, (A×B)y={A,y∈B,∅,y∉B.

[A2]

For fixed x, ((X×Y)∖E)x=Y∖Ex,(⋃n≥1En)x=⋃n≥1(En)x, and the analogous formulas hold for vertical sections.

Proof

technique · direct
1.1A1A2L1L2

Fix x∈X and let Mx be the family of sets F⊆X×Y such that Fx∈B. By [A1], every measurable rectangle belongs to Mx. By [A2], Mx is a sigma-algebra on X×Y. Since [L1] says A⊗B is generated by the measurable rectangles, [L2] gives A⊗B⊆Mx. Therefore Ex∈B.

2.1step 1.1L1L2A1A2∎

Fix y∈Y and let Ny be the family of sets F⊆X×Y such that Fy∈A. The same argument shows that Ny is a sigma-algebra containing all measurable rectangles, hence all of A⊗B. Therefore Ey∈A. Since x and y were arbitrary, every horizontal and vertical section of E is measurable.

TheoremStatement: AI-adaptedProof: AI-generatedprecheck passjudge pass (gpt-5.6-terra)audited 2026-08-29Open item page →

Every section of a product-measurable function is measurable

Statement

Let (X,A) and (Y,B) be measurable spaces, and let f:X×Y→R‾ be (A⊗B,B(R‾))-measurable. Then fx:Y→R‾ is B-measurable for every x∈X, and fy:X→R‾ is A-measurable for every y∈Y.

Facts & Assumptions

Given: Measurable spaces (X,A) and (Y,B), and a product-measurable function f:X×Y→R‾.

[L1]

A function into R‾ is measurable once the preimages of a generating family for B(R‾) are measurable. (A generating family on the codomain suffices to test measurability)

[L2]

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

[A1]

For every Borel set U⊆R‾, fx−1(U)=(f−1(U))x,(fy)−1(U)=(f−1(U))y.

Proof

technique · direct
1.1L1A1L2

Fix x∈X and let G be a generating family for B(R‾). For each U∈G, the set f−1(U) is product-measurable, so [L2] and [A1] give fx−1(U)=(f−1(U))x∈B. By [L1], fx is therefore B-measurable.

2.1step 1.1A1L1L2∎

Fix y∈Y. The same argument gives (fy)−1(U)=(f−1(U))y∈A for every generator U∈G, so [L1] implies that fy is A-measurable. Thus every horizontal and vertical section of f is measurable.

False statementConstruction: AI-adaptedVerification: AI-generatedprecheck passjudge pass (gpt-5.6-terra)audited 2026-08-29Open item page →

FALSE: if every horizontal and vertical section is measurable, then the set is product-measurable

Statement

If E⊆X×Y has measurable horizontal sections Ex for every x∈X and measurable vertical sections Ey for every y∈Y, then E∈A⊗B.

Facts & Assumptions

Given: Assume the Axiom of Countable Choice. Let X be the set of countable ordinals, let M be the sigma-algebra of countable and cocountable subsets of X, and let E:={(x,y)∈X×X:y<x}.

[L1]

Every section of a product-measurable set is measurable. (Every section of a product-measurable set is measurable)

[L2]

A sigma-algebra is closed under complements and countable unions, and under countable choice a countable union of countable sets is countable. (Sigma-algebras, The Axiom of Countable Choice (ACω), Countable unions of at most countable sets, assuming ACω)

[L3]

For sigma-finite measures, the two iterated section-measure integrals of a product-measurable set agree. (For sigma-finite measures, the two section-measure integrals of a measurable set agree)

[A1]

Define ν on M by ν(A)=0 for countable A and ν(A)=1 for cocountable A. The same countable-union argument as in [L2] shows that ν is a finite measure on (X,M).

Refutation

technique · direct
1.1givenL2

For each x∈X, the section Ex={y:y<x} is countable by the choice of X, hence measurable for M. For each y∈X, the section Ey={x:y<x} has countable complement {x:x≤y}, hence is cocountable and measurable.

2.1L1L3A1step 1.1∎

Suppose for contradiction that E were product-measurable for M⊗M. Since ν(X)=1, the measure ν is finite and hence sigma-finite, so [L3] would give ∫Xν(Ex) dν=∫Xν(Ey) dν. But step 1.1 makes ν(Ex)=0 for every x and ν(Ey)=1 for every y, so the two sides are 0 and 1, a contradiction. Therefore E is not product-measurable, even though all of its sections are measurable. This does not contradict [L1], which proves only the forward implication from product-measurability to section measurability.

PropositionStatement: AI-adaptedProof: AI-generatedprecheck passverified 2026-09-08 (Codex)Open item page →

For sigma-finite measures, the section-measure functions are measurable

Statement

Let (X,A,μ) and (Y,B,ν) be sigma-finite measure spaces, and let E∈A⊗B. Then the functions

x↦ν(Ex),y↦μ(Ey)

are measurable from X and Y into [0,∞].

Facts & Assumptions

Given: Sigma-finite measure spaces (X,A,μ) and (Y,B,ν), and a set E∈A⊗B.

[L1]

Finite disjoint unions of measurable rectangles form an algebra that generates A⊗B. (Finite disjoint unions of measurable rectangles form an algebra generating the product sigma-algebra)

[L2]

If an algebra generates a sigma-algebra, then its monotone class is that same sigma-algebra. (The monotone class generated by an algebra equals the sigma-algebra it generates)

[L3]
[L4]

Measures are continuous on increasing sequences, and on decreasing sequences whose first term has finite measure. (Continuity from below for measures, Continuity from above when one set has finite measure)

[A1]

Since ν is sigma-finite, there are measurable sets Ym↑Y with ν(Ym)<∞ for every m. Likewise there are measurable Xn↑X with μ(Xn)<∞.

[A2]

If Fk↑F, then (Fk)x↑Fx and ν((Fk)x∩Ym)↑ν(Fx∩Ym) for every x. If Fk↓F, then (Fk)x∩Ym↓Fx∩Ym, and continuity from above on the finite-measure space Ym gives ν((Fk)x∩Ym)↓ν(Fx∩Ym).

Proof

technique · direct
1.1L1A1givenalgebra

Fix m≥1 and let Cm consist of product-measurable sets F for which x↦ν(Fx∩Ym) is measurable. If F is a finite disjoint union of rectangles Aj×Bj, its sections are disjoint unions of those Bj with x∈Aj. Finite additivity therefore gives ν(Fx∩Ym)=∑jν(Bj∩Ym)1Aj(x). All coefficients are finite by [A1]. On each of the finitely many measurable Boolean atoms of the sets Aj, this function is constant; hence the inverse image of any Borel set is a finite union of those atoms. The empty union gives the zero function. Thus the entire generating algebra from [L1], not merely its individual rectangles, is contained in Cm.

2.1L1L2L3L4A1A2step 1.1

Sections commute with increasing unions and decreasing intersections. For an increasing sequence in Cm, [L4] identifies the section-measure function of its union with the pointwise increasing limit. For a decreasing sequence, all restricted sections have measure at most ν(Ym)<∞, so [L4] likewise identifies the function of the intersection with the decreasing limit. In both cases [L3] makes that limit measurable. Thus Cm is a monotone class, and [L1], [L2] and step 1.1 imply that it contains every product-measurable set.

3.1A1L3L4step 2.1

Applying step 2.1 to E shows that gm(x):=ν(Ex∩Ym) is measurable for every m. Since Ym↑Y, [L4] gives gm(x)↑ν(Ex) for each x, and [L3] proves measurability of x↦ν(Ex).

4.1A1L3L4step 1.1step 2.1step 3.1∎

Interchanging the two factors and using the finite-measure exhaustion Xn↑X proves measurability of y↦μ(Ey) by the same argument. Therefore both section-measure functions are measurable.

TheoremStatement: AI-adaptedProof: AI-generatedprecheck passverified 2026-09-08 (Codex)Open item page →

For sigma-finite measures, the two section-measure integrals of a measurable set agree

Statement

Let (X,A,μ) and (Y,B,ν) be sigma-finite measure spaces, and let E∈A⊗B. Then

∫Xν(Ex) dμ=∫Yμ(Ey) dν.

Facts & Assumptions

Given: Sigma-finite measure spaces (X,A,μ) and (Y,B,ν), and a set E∈A⊗B.

[L1]

The section-measure functions x↦ν(Ex) and y↦μ(Ey) are measurable. (For sigma-finite measures, the section-measure functions are measurable)

[L2]

Finite disjoint unions of measurable rectangles form an algebra generating A⊗B. (Finite disjoint unions of measurable rectangles form an algebra generating the product sigma-algebra)

[L3]

The monotone class generated by an algebra coincides with the generated sigma-algebra. (The monotone class generated by an algebra equals the sigma-algebra it generates)

[L4]

Monotone convergence allows integrals of increasing nonnegative functions to pass to the limit. (Monotone convergence for the integral)

[A1]

Since μ and ν are sigma-finite, there are measurable exhaustions Xn↑X and Yn↑Y with μ(Xn),ν(Yn)<∞.

Proof

technique · direct
1.1L2L3A1

Fix n,m≥1. Let Dn,m be the family of measurable subsets F⊆Xn×Ym such that ∫Xnν(Fx) dμ=∫Ymμ(Fy) dν. If F=(A×B)∩(Xn×Ym), then Fx=(B∩Ym) for x∈A∩Xn and ∅ otherwise, so both integrals equal μ(A∩Xn)ν(B∩Ym). Finite additivity gives the same equality for the algebra of [L2].

2.1L1L2L3L4A1step 1.1

If Fk↑F inside Xn×Ym, then [L1] and [L4] give ∫Xnν((Fk)x) dμ↑∫Xnν(Fx) dμ, and similarly on Ym. Hence Dn,m is closed under increasing unions. For F∈Dn,m, put Fc=(Xn×Ym)∖F. Each section-integral of Fc equals the finite number μ(Xn)ν(Ym) minus the corresponding section-integral of F. This follows by adding the complementary sections and integrating; all quantities are finite because they are bounded by that finite product. Thus Fc∈Dn,m. If Fk↓F, their relative complements increase to Fc; closure under increasing unions and complements therefore gives F∈Dn,m. The class is now proved monotone in both directions and contains the relative rectangle algebra by step 1.1. Applying [L2] and [L3] on Xn×Ym yields every product-measurable subset of that rectangle.

3.1step 2.1A1

Put En,m:=E∩(Xn×Ym). Step 2.1 gives ∫Xnν((En,m)x) dμ=∫Ymμ((En,m)y) dν. Now (En,m)x=Ex∩Ym for x∈Xn and ∅ otherwise, so as n,m→∞ the two integrands increase pointwise to ν(Ex) and μ(Ey).

4.1L4step 3.1L1∎

Applying [L4] on both sides of step 3.1 and then letting n,m→∞ gives ∫Xν(Ex) dμ=∫Yμ(Ey) dν. This is the claimed equality.

DefinitionDefinition: AI-adaptedProof: Not applicablejudge pass (gpt-5.6-terra)audited 2026-08-29Open item page →

The product measure of two sigma-finite measure spaces

Definition

Let (X,A,μ) and (Y,B,ν) be sigma-finite measure spaces. For E∈A⊗B, define

(μ×ν)(E):=∫Xν(Ex) dμ=∫Yμ(Ey) dν.

The two displayed integrals are well-defined by For sigma-finite measures, the section-measure functions are measurable and equal by For sigma-finite measures, the two section-measure integrals of a measurable set agree. This is the product measure of μ and ν.

TheoremStatement: AI-adaptedProof: AI-generatedprecheck passverified 2026-09-23 (gpt-6-sol)Open item page →

For sigma-finite factors, the product measure exists, has the rectangle formula, is sigma-finite, and is unique

Statement

Let (X,A,μ) and (Y,B,ν) be sigma-finite measure spaces. Then:

  1. the set function E↦(μ×ν)(E) of The product measure of two sigma-finite measure spaces is a measure on A⊗B;
  2. for measurable rectangles, (μ×ν)(A×B)=μ(A)ν(B), with the nonnegative extended-product convention 0⋅∞=∞⋅0=0;
  3. the measure μ×ν is sigma-finite; and
  4. it is the unique measure on A⊗B with the rectangle formula.

Facts & Assumptions

Given: Sigma-finite measure spaces (X,A,μ) and (Y,B,ν).

[L1]

For every product-measurable set E, (μ×ν)(E)=∫Xν(Ex) dμ=∫Yμ(Ey) dν. (The product measure of two sigma-finite measure spaces)

[L2]

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

[L3]

A measure is determined by its values on a sigma-finite generating pi-system. (Measures agreeing on a generating pi-system are equal under an increasing finite-measure exhaustion from that pi-system)

[L4]

The nonnegative integral is additive for finite sums of nonnegative measurable functions. (Additivity of the nonnegative Lebesgue integral)

[L5]

The nonnegative integral agrees with the simple integral, whose zero coefficient on a null cell contributes zero even when another factor is infinite (The nonnegative integral agrees with the simple integral on simple functions, The integral of a nonnegative simple function).

[A1]

Measurable rectangles form a pi-system that generates A⊗B.

[A2]

Since μ and ν are sigma-finite, there are measurable exhaustions Xn↑X and Yn↑Y with μ(Xn),ν(Yn)<∞.

Proof

technique · direct
1.1L1L5

If E=A×B is a measurable rectangle, then (A×B)x={B,x∈A,∅,x∉A. Thus its section-measure function is ν(B)1A, where the value outside A is zero even when ν(B)=∞. The simple-function integral [L5] gives (μ×ν)(A×B)=∫Xν((A×B)x) dμ=μ(A)ν(B) with 0⋅∞=0 when μ(A)=0, and symmetrically when ν(B)=0. This proves the rectangle formula in every extended-value case.

1.2L1L2L4

Let E1,E2,… be pairwise disjoint measurable subsets of X×Y, and put FN:=⋃k≤NEk. Then (FN)x=⋃k≤N(Ek)x is a disjoint union, so ν((FN)x)=∑k≤Nν((Ek)x) for every x. The section functions are nonnegative measurable, and finite additivity of their integrals gives (μ×ν)(FN)=∫X∑k≤Nν((Ek)x) dμ=∑k≤N(μ×ν)(Ek). Since the section functions for FN increase pointwise to that of ⋃k≥1Ek, [L2] gives (μ×ν)(⋃k≥1Ek)=∑k≥1(μ×ν)(Ek). The empty set has product measure zero, so μ×ν is a measure.

2.1A2step 1.1

By [A2] and step 1.1, each rectangle Xn×Yn has finite product measure (μ×ν)(Xn×Yn)=μ(Xn)ν(Yn)<∞, and ⋃n(Xn×Yn)=X×Y. Hence μ×ν is sigma-finite.

3.1A1L3step 1.1step 2.1∎

Let ρ be another measure on A⊗B with the same rectangle formula. Step 1.1 shows that ρ and μ×ν agree on the generating pi-system of measurable rectangles, and step 2.1 gives the required sigma-finite exhaustion. Therefore [L3] implies ρ=μ×ν on all of A⊗B. This proves existence, the rectangle formula, sigma-finiteness, and uniqueness.

False statementConstruction: AI-adaptedVerification: AI-generatedprecheck passjudge pass (gpt-5.6-terra)audited 2026-08-29Open item page →

FALSE: the rectangle formula determines a unique product measure without any sigma-finiteness hypothesis

Statement

For arbitrary measure spaces, any two measures on A⊗B that agree on every measurable rectangle must agree everywhere.

Facts & Assumptions

Given: Lebesgue measure μ on [0,1], counting measure ν on [0,1], the diagonal D:={(x,y)∈[0,1]2:x=y}, and the two measures ρ,τ on the same product sigma-algebra supplied by the standard non-sigma-finite Lebesgue/counting construction in the listed Tao source, with ρ(A×B)=μ(A)ν(B)=τ(A×B) on measurable rectangles and ρ(D)=1≠0=τ(D).

[L1]

Under sigma-finiteness, the rectangle formula does determine a unique product measure. (For sigma-finite factors, the product measure exists, has the rectangle formula, is sigma-finite, and is unique)

Refutation

technique · direct
1.1given

The witness in the Given line satisfies exactly the hypothesis of the displayed claim: ρ and τ are measures on the same product sigma-algebra and agree on every measurable rectangle.

2.1L1givenstep 1.1∎

The same witness also satisfies ρ(D)=1≠0=τ(D), so ρ≠τ. Hence the displayed universal uniqueness claim is false. This shows why the sigma-finiteness hypothesis in [L1] is essential.

TheoremStatement: AI-adaptedProof: AI-generatedprecheck passverified 2026-09-23 (gpt-6-sol)Open item page →

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 x↦∫Yfx dν and y↦∫Xfy dμ are measurable, and

∫X×Yf d(μ×ν)=∫X(∫Yfx dν)dμ=∫Y(∫Xfy dμ)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×Y1E d(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)

[L5]

The nonnegative integral is additive for finite sums of measurable nonnegative functions. (Additivity of the nonnegative Lebesgue integral)

Proof

technique · direct
1.1L2L5

If s is a nonnegative simple function, write s=∑j=1mcj1Ej with cj≥0 and measurable sets Ej. Applying [L2] to each indicator 1Ej and summing by [L5] yields ∫s d(μ×ν)=∫X(∫Ysx dν)dμ=∫Y(∫Xsy dμ)dν. The inner integral functions are measurable because the same is true for each 1Ej and simple combinations preserve measurability.

2.1L1L3L4step 1.1∎

Choose simple functions sn↑f by [L3]. Then for each x and y one has (sn)x↑fx and (sn)y↑fy, so [L4] gives ∫Y(sn)x dν↑∫Yfx dν,∫X(sn)y dμ↑∫Xfy dμ. Applying [L4] once more to the equalities of step 1.1 yields the stated measurability and the equality of all three integrals.

False statementConstruction: AI-adaptedVerification: AI-generatedprecheck passjudge pass (gpt-5.6-terra)audited 2026-08-29Open item page →

FALSE: Tonelli's theorem still holds without any sigma-finiteness hypothesis

Statement

For arbitrary measure spaces, every nonnegative product-measurable function satisfies Tonelli's theorem.

Facts & Assumptions

Given: Lebesgue measure μ on [0,1], counting measure ν on [0,1], the diagonal D:={(x,y)∈[0,1]2:x=y}, and the indicator function f:=1D.

[L1]

Tonelli's theorem holds on sigma-finite product spaces. (Tonelli's theorem for nonnegative measurable functions on a sigma-finite product)

[A1]

Counting measure on the uncountable set [0,1] is not sigma-finite in the sense of Finite, sigma-finite, and semifinite measures.

[A2]

For every x,y∈[0,1], the diagonal sections are Dx={x} and Dy={y}.

Refutation

technique · direct
1.1A1algebra

The diagonal D is closed in [0,1]2, so f=1D is a nonnegative measurable function; by [A1], it lives on a product space outside the sigma-finite scope of [L1].

1.2A2algebra

For fixed x∈[0,1], [A2] gives ν(Dx)=1, so ∫[0,1]ν(Dx) dμ(x)=∫011 dx=1.

1.3A2algebra

For fixed y∈[0,1], [A2] gives μ(Dy)=0, so ∫[0,1]μ(Dy) dν(y)=∫[0,1]0 dν=0.

2.1L1step 1.1step 1.2step 1.3∎

Steps 1.2 and 1.3 give unequal iterated integrals for the same nonnegative measurable function on a non-sigma-finite product space. Hence the displayed universal claim is false, and [L1] cannot be extended by simply deleting sigma-finiteness.

TheoremStatement: AI-adaptedProof: AI-generatedprecheck passaudited 2026-08-29Open item page →

Fubini's theorem for L^1 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→C belong to L1(μ×ν). Then:

  1. for μ-almost every x, the section fx belongs to L1(ν);
  2. for ν-almost every y, the section fy belongs to L1(μ);
  3. after assigning the value 0 on the exceptional parameter sets, the section-integral functions are integrable; and
  4. the three integrals agree: ∫X×Yf d(μ×ν)=∫X(∫Yfx dν)dμ=∫Y(∫Xfy dμ)dν.

Facts & Assumptions

Given: Sigma-finite measure spaces (X,A,μ) and (Y,B,ν), and a function f∈L1(μ×ν).

[L1]

Tonelli's theorem holds for nonnegative measurable functions on X×Y. (Tonelli's theorem for nonnegative measurable functions on a sigma-finite product)

[L2]

A complex-valued function belongs to L1 exactly when its absolute value has finite integral. (The class L1(μ) of integrable functions)

[L3]

The Lebesgue integral is linear on L1. (The Lebesgue integral is linear on L1(μ))

[L4]

The triangle inequality gives ∣∫g dη∣≤∫∣g∣ dη for every integrable function g. (The modulus of an integral is bounded by the integral of the modulus)

Proof

technique · direct
1.1L1L2

By [L2], the function ∣f∣ is nonnegative measurable, and [L1] gives ∫X(∫Y∣fx∣ dν)dμ=∫X×Y∣f∣ d(μ×ν)<∞. Therefore ∫Y∣fx∣ dν<∞ for μ-almost every x, so fx∈L1(ν) for μ-almost every x. The same argument with the variables reversed gives fy∈L1(μ) for ν-almost every y and shows that the section integrals of ∣f∣ are integrable.

2.1step 1.1L4

For almost every x from step 1.1, [L4] gives ∣∫Yfx dν∣≤∫Y∣fx∣ dν. Define the section integral to be 0 on the exceptional null set where fx∉L1(ν). The right-hand side is integrable over X by step 1.1, so this extended section-integral function is integrable. The same convention and conclusion hold for y↦∫Xfy dμ.

3.1step 1.1step 2.1L1L3∎

Write f=u−v+i(p−q), where u,v,p,q≥0 are the positive and negative parts of the real and imaginary parts of f. Each of u,v,p,q is integrable because ∣u∣,∣v∣,∣p∣,∣q∣≤∣f∣. Applying [L1] to these four nonnegative functions and recombining with [L3] yields the stated equality of the three integrals.

RemarkRemark: AI-adaptedProof: Not applicablejudge pass (gpt-5.6-terra)audited 2026-08-29Open item page →

To use Fubini safely, first use Tonelli on |f|

The safe workflow is:

  1. apply Tonelli's theorem for nonnegative measurable functions on a sigma-finite product to ∣f∣;
  2. check that the resulting iterated integral is finite; then
  3. invoke Fubini's theorem for L^1 functions on a sigma-finite product.

This is the point of the absolute-integrability hypothesis in Fubini's theorem. Without it, the iterated integrals may exist separately and still disagree.

DefinitionDefinition: AI-adaptedProof: Not applicablejudge pass (gpt-5.6-terra)audited 2026-08-29Open item page →

The completed product measure

Definition

Assume the Axiom of Countable Choice (The Axiom of Countable Choice (ACω)). Let (X,A,μ) and (Y,B,ν) be sigma-finite measure spaces. The completed product measure is the completion of the measure μ×ν on (X×Y,A⊗B):

μ×ν‾:=the completion of μ×ν.

Its sigma-algebra consists of sets that differ from an (A⊗B)-measurable set by a subset of a (μ×ν)-null set, exactly as in The completion domain and proposed completed set function of a measure space.

TheoremStatement: AI-adaptedProof: AI-generatedprecheck passverified 2026-09-23 (gpt-6-sol)Open item page →

Tonelli and Fubini for the completed product, with only almost-everywhere section measurability

Statement

Assume the Axiom of Countable Choice (The Axiom of Countable Choice (ACω)), and let μ×ν‾ be the completed product of two sigma-finite measure spaces.

  1. If f:X×Y→[0,∞] is μ×ν‾-measurable, there are measurable null sets A⊆X and B⊆Y such that fx is B‾-measurable for x∉A and fy is A‾-measurable for y∉B. Define If(x)=∫Yfx dν‾ for x∉A and If(x)=0 on A; define Jf(y)=∫Xfy dμ‾ for y∉B and Jf(y)=0 on B. Then If,Jf are measurable and ∫f dμ×ν‾=∫XIf dμ=∫YJf dν.
  2. If f∈L1(μ×ν‾), there are measurable null sets A⊆X and B⊆Y such that the sections are measurable and integrable outside them. Define If,Jf by the same section integrals outside A,B and by zero on A,B. They are measurable and integrable, and the same equality holds.

Facts & Assumptions

Given: The Axiom of Countable Choice, two sigma-finite measure spaces, their completed product μ×ν‾, and either a nonnegative μ×ν‾-measurable function f or an integrable function f∈L1(μ×ν‾).

[L1]

Assuming countable choice, a function measurable for a completion is almost everywhere equal to one measurable for the original sigma-algebra. (A function measurable for a completion is almost everywhere equal to one measurable for the original sigma-algebra)

[L4]

On a complete measure space, almost-everywhere equality with a measurable function implies measurability. (On a complete measure space, equality almost everywhere preserves measurability)

[L5]

Integrable complex functions have integrable real and imaginary parts. (Integrable real and complex functions, and their integrals)

Proof

technique · direct
1.1L1choose

In the nonnegative branch, [L1] gives a product-measurable extended-real function g such that f=g almost everywhere for μ×ν‾. Let N:={(x,y):f(x,y)≠g(x,y)}, so μ×ν‾(N)=0. By the completion definition, choose a product-measurable null set Z with N⊆Z.

2.1L2L4step 1.1

Apply Tonelli in [L2] to 1Z. Since (μ×ν)(Z)=0, it gives ∫Xν(Zx) dμ=0,∫Yμ(Zy) dν=0. The functions x↦ν(Zx) and y↦μ(Zy) are measurable, so A:={x:ν(Zx)>0} and B:={y:μ(Zy)>0} are measurable null sets. For x∉A, fx=gx outside the null section Zx; [L4] makes fx measurable for the completed factor measure. The analogous statement holds for y∉B.

3.1L2L3step 1.1step 2.1

In the nonnegative case, replace the product-measurable representative g by g+=max⁡(g,0). Since f≥0 and f=g outside Z, one has f=g+ there, both on the product and on every section outside A,B. Apply Tonelli [L2] to g+. Define If and Jf to equal the section integrals of f outside A,B and zero on A,B as in the statement. They agree there with the measurable Tonelli section-integral functions of g+, so are measurable and have the same outer integrals. By [L3], the completed integral of f equals the product integral of g+. Tonelli now gives the asserted three-way equality.

4.1L1L2L3L4L5step 2.1∎

If f∈L1(μ×ν‾), apply [L1] separately to Re⁡f and Im⁡f, obtaining product-measurable extended-real functions u,v equal to those finite parts almost everywhere. Their nonfinite-value sets are product-null; set u,v to zero there, making them finite real-valued product-measurable functions. Put g:=u+iv. The discrepancy set {f≠g} is contained in a product-measurable null set Z by the completion definition, so g=f outside Z. By [L3] applied to ∣f∣ and ∣g∣, g∈L1(μ×ν). By Fubini [L2], the measurable sets where ∫∣gx∣ dν=∞ or ∫∣gy∣ dμ=∞ are factor-null. Apply the Tonelli argument of step 2.1 to this new Z, obtaining measurable factor-null sets A,B, and enlarge them by these nonintegrability sets. Outside the enlarged sets, apply [L4] separately to the real and imaginary parts to make each f section measurable; its almost-everywhere equality to the corresponding integrable g section then makes it integrable with the same integral. Define If,Jf by these section integrals there and zero on the exceptional sets. They are measurable, integrable, and equal almost everywhere to the Fubini section-integral functions for g. By [L3], their integrals equal the completed product integral of f.

False statementConstruction: AI-adaptedVerification: AI-generatedprecheck passjudge pass (gpt-5.6-terra)audited 2026-08-29Open item page →

FALSE: every section of a completed-product measurable function is measurable

Statement

If f is measurable for the completed product μ×ν‾, then fx is measurable for every x and fy is measurable for every y.

Facts & Assumptions

Given: Lebesgue measure λ on R, a non-Lebesgue-measurable set N⊆R, the set E:={0}×N⊆R2, and the indicator function f:=1E.

[L1]

For completed products, section measurability is guaranteed only for almost every parameter. (Tonelli and Fubini for the completed product, with only almost-everywhere section measurability)

[L2]

The completed product sigma-algebra contains every subset of a (λ×λ)-null set. (The completed product measure)

[L3]

On measurable rectangles, the product measure satisfies (λ×λ)(A×B)=λ(A)λ(B). (For sigma-finite factors, the product measure exists, has the rectangle formula, is sigma-finite, and is unique)

Refutation

technique · direct
1.1L3algebra

For each n≥1, the rectangle Zn:={0}×[−n,n] satisfies (λ×λ)(Zn)=λ({0})λ([−n,n])=0 by [L3], so Z:={0}×R=⋃n≥1Zn is (λ×λ)-null.

2.1L2step 1.1

Because E⊆Z, [L2] puts E in the completed product sigma-algebra, so f=1E is measurable for the completed product.

3.1L1step 2.1∎

The section at 0 is f0=1N, which is not measurable because N is not Lebesgue measurable. Thus the displayed claim fails even though f is measurable for the completed product, and [L1] is sharp.

TheoremStatement: AI-adaptedProof: AI-generatedprecheck passjudge pass (gpt-5.6-terra)audited 2026-08-29Open item page →

The Borel product of R^m and R^n is the Borel sigma-algebra of R^{m+n}

Statement

Let m,n≥1. Under the identification Rm+n=Rm×Rn, one has B(Rm)⊗B(Rn)=B(Rm+n).

Facts & Assumptions

Given: Positive integers m,n and the identification Rm+n=Rm×Rn.

[L1]

The Borel sigma-algebra on a topological space is the sigma-algebra generated by its open sets. (The Borel sigma-algebra of a topological space)

[L2]

Continuous maps pull Borel sets back to Borel sets. (A continuous map has Borel preimages of Borel sets)

[A1]

The coordinate projections π1:Rm+n→Rm and π2:Rm+n→Rn are continuous.

[A2]

Every open set in Rm+n is a countable union of open rectangles U×V with U⊆Rm and V⊆Rn open.

Proof

technique · direct
1.1A1L2

If A⊆Rm and B⊆Rn are Borel, then A×B=π1−1(A)∩π2−1(B), so [L2] makes A×B Borel in Rm+n. Therefore every measurable rectangle for B(Rm)⊗B(Rn) belongs to B(Rm+n), and hence B(Rm)⊗B(Rn)⊆B(Rm+n).

2.1step 1.1A2L1∎

By [A2], every open set in Rm+n is a countable union of open rectangles, hence belongs to B(Rm)⊗B(Rn). Since [L1] says a Borel sigma-algebra is generated by the open sets, this gives the reverse inclusion. Combining with step 1.1 proves the equality.

RemarkRemark: AI-adaptedProof: Not applicablejudge pass (gpt-5.6-terra)audited 2026-08-29Open item page →

The equality B(X) tensor B(Y) = B(X x Y) needs second countability

The proof of The Borel product of R^m and R^n is the Borel sigma-algebra of R^{m+n} uses the fact that every open subset of the product is a countable union of open rectangles. That countable basis input is exactly where second countability enters. Without it, B(X)⊗B(Y) can be strictly smaller than B(X×Y).

TheoremStatement: AI-adaptedProof: AI-generatedverified 2026-09-26 (gpt-6-sol)Open item page →

On Borel subsets of R^{m+n}, the product lambda_m times lambda_n agrees with lambda_{m+n}

Statement

Assume the Axiom of Countable Choice (The Axiom of Countable Choice (ACω)). Let m,n≥1. Under the identification Rm+n=Rm×Rn, the product measure λm×λn and the Euclidean Lebesgue measure λm+n agree on every Borel subset of Rm+n.

Facts & Assumptions

Given: The Axiom of Countable Choice, positive integers m,n, and the identification Rm+n=Rm×Rn.

[L1]

The Borel sigma-algebra on Rm+n is B(Rm)⊗B(Rn). (The Borel product of R^m and R^n is the Borel sigma-algebra of R^{m+n})

[L2]

The product measure on sigma-finite spaces exists and satisfies the rectangle formula. (For sigma-finite factors, the product measure exists, has the rectangle formula, is sigma-finite, and is unique)

[L5]

Two measures that agree on a sigma-finite generating pi-system agree on the generated sigma-algebra. (Measures agreeing on a generating pi-system are equal under an increasing finite-measure exhaustion from that pi-system)

[A1]

Rational half-open boxes, together with the empty set, form a generating pi-system for B(Rm+n). The increasing boxes QN=(−N,N]m+n exhaust the space and have finite measure for both measures in the Statement.

Proof

technique · direct
1.1L2L3

For d=m,n, the cubes (−N,N]d exhaust Rd and have finite measure by [L3], so the sigma-finite product theorem [L2] applies. Let Q=∏i<m+n(ai,bi] be a rational half-open box. Split it as Q=A×B with A⊆Rm and B⊆Rn. Then the rectangle formula of [L2] and [L3] give (λm×λn)(Q)=λm(A)λn(B)=∏i<m+n(bi−ai)=λm+n(Q).

2.1A1L1L2L3L5step 1.1∎

Each QN from [A1] has finite λm+n-measure by [L3], and finite product measure by [L2] and [L3]; step 1.1 shows these values agree. The same step gives agreement on the whole generating pi-system, while [L1] identifies its generated sigma-algebra with B(Rm+n). Therefore [L5] implies λm×λn=λm+n on every Borel set.

TheoremStatement: AI-adaptedProof: AI-generatedprecheck passaudited 2026-08-29Open item page →

The Euclidean Lebesgue measure is the completion of the product of the factor Lebesgue measures

Statement

Assume the Axiom of Countable Choice (The Axiom of Countable Choice (ACω)). Let m,n≥1. Under the identification Rm+n=Rm×Rn, the Lebesgue measure λm+n is the completion of the product measure λm×λn.

Facts & Assumptions

Given: The Axiom of Countable Choice and positive integers m,n.

[L1]

On Borel sets, λm×λn agrees with λm+n. (On Borel subsets of R^{m+n}, the product lambda_m times lambda_n agrees with lambda_{m+n})

[L2]

Assuming countable choice, the full Lebesgue sigma-algebra is the completion of the Borel Lebesgue measure. (L(Rn) is exactly the completion of the restriction of λn to the Borel sets)

[L3]

For sigma-finite factors, the product measure is the unique measure on the product sigma-algebra with the rectangle formula. (For sigma-finite factors, the product measure exists, has the rectangle formula, is sigma-finite, and is unique)

[L4]

Assuming countable choice, Euclidean Lebesgue measure is sigma-finite. (Lebesgue measure is sigma-finite, and every metrically bounded subset of Rn has finite outer measure)

[L6]

The completed product measure is the completion of the product measure. (The completed product measure)

Proof

technique · direct
1.1L1L2L3L4algebra

Let A∈L(Rm) and B∈L(Rn). By [L2], choose Borel cores A0,B0 and Borel null hulls Z,W such that A△A0⊆Z and B△B0⊆W. The slabs Z×Rn and Rm×W are Euclidean null: for example, Z×Rn=⋃k≥1Z×[−k,k]n, and [L1], [L3], and [L4] give Euclidean measure 0 to each Borel rectangle in this union. Since (A×B)△(A0×B0)⊆(Z×Rn)∪(Rm×W), [L2] makes A×B Euclidean Lebesgue measurable.

2.1step 1.1L1L2L3L4L5

Step 1.1 puts every measurable rectangle in L(Rm+n), so L(Rm)⊗L(Rn)⊆L(Rm+n). Let ρ be the restriction of λm+n to this product sigma-algebra. For the rectangle in step 1.1, completeness [L5] and the null symmetric difference give ρ(A×B)=λm+n(A0×B0); [L1] and [L2] identify this with λm(A)λn(B). Thus ρ has the product rectangle formula. By [L4] the factors are sigma-finite, so uniqueness in [L3] gives ρ=λm×λn.

3.1L1L2L5L6step 2.1∎

Because the product sigma-algebra is contained in the complete Euclidean Lebesgue sigma-algebra and the measures agree there by step 2.1, its completion is contained in L(Rm+n). Conversely, if E∈L(Rm+n), [L2] gives a Borel C and a Borel null set Z with E△C⊆Z. The Borel sets C,Z belong to the product sigma-algebra, and [L1] and step 2.1 give (λm×λn)(Z)=λm+n(Z)=0. Hence E belongs to the completion of the product measure. The domains and measures therefore coincide, which is exactly the completion claim of [L6].

False statementConstruction: AI-adaptedVerification: AI-generatedprecheck passjudge pass (gpt-5.6-terra)audited 2026-08-29Open item page →

FALSE: the product of two complete measure spaces is complete

Statement

If (X,A,μ) and (Y,B,ν) are complete measure spaces, then the product measure space (X×Y,A⊗B,μ×ν) is complete.

Facts & Assumptions

Given: Lebesgue measure λ on R, a non-Lebesgue-measurable set N⊆R, the set E:={0}×N⊆R2, and the line Z:={0}×R.

[L1]

The completed product measure is generally a genuine completion of the uncompleted product measure. (The Euclidean Lebesgue measure is the completion of the product of the factor Lebesgue measures)

[L2]

Every section of a product-measurable set is measurable. (Every section of a product-measurable set is measurable)

[L3]

On measurable rectangles, the product measure satisfies (λ×λ)(A×B)=λ(A)λ(B). (For sigma-finite factors, the product measure exists, has the rectangle formula, is sigma-finite, and is unique)

Refutation

technique · direct
1.1L3algebra

For each n≥1, the rectangle Zn:={0}×[−n,n] satisfies (λ×λ)(Zn)=λ({0})λ([−n,n])=0 by [L3], so Z=⋃n≥1Zn is (λ×λ)-null.

2.1L1step 1.1

Because E⊆Z, [L1] makes E Lebesgue measurable in R2.

3.1L1L2step 2.1∎

If E belonged to L(R)⊗L(R), its horizontal section at 0 would be E0=N, which is not Lebesgue measurable, contradicting [L2]. Thus the product sigma-algebra misses a subset of a product-null set, so the product of two complete Lebesgue spaces need not be complete. This is exactly why [L1] needs an actual completion step.

False statementConstruction: AI-adaptedVerification: AI-generatedprecheck passaudited 2026-08-29Open item page →

FALSE: the product Lebesgue sigma-algebra is the full Euclidean Lebesgue sigma-algebra

Statement

Assume the Axiom of Countable Choice (The Axiom of Countable Choice (ACω)). For all m,n≥1, L(Rm)⊗L(Rn)=L(Rm+n).

Facts & Assumptions

Given: The Axiom of Countable Choice, Lebesgue measure λ on R, a non-Lebesgue-measurable set N⊆R, the set E:={0}×N⊆R2, and the line Z:={0}×R.

[L1]

The Euclidean Lebesgue measure is the completion of the product measure. (The Euclidean Lebesgue measure is the completion of the product of the factor Lebesgue measures)

[L2]

Every section of a product-measurable set is measurable. (Every section of a product-measurable set is measurable)

[L3]

On measurable rectangles, the product measure satisfies (λ×λ)(A×B)=λ(A)λ(B). (For sigma-finite factors, the product measure exists, has the rectangle formula, is sigma-finite, and is unique)

Refutation

technique · direct
1.1L3algebra

For each n≥1, the rectangle Zn:={0}×[−n,n] satisfies (λ×λ)(Zn)=λ({0})λ([−n,n])=0 by [L3], so Z=⋃n≥1Zn is (λ×λ)-null.

2.1L1step 1.1

Because E⊆Z, [L1] makes E Lebesgue measurable in R2.

3.1L1L2step 2.1∎

If the displayed equality were true, then E would belong to L(R)⊗L(R). But then [L2] would force the horizontal section E0=N to be Lebesgue measurable, a contradiction. Therefore the product sigma-algebra is strictly smaller than the full Euclidean Lebesgue sigma-algebra. The correct statement is the completion statement of [L1].

TheoremStatement: AI-adaptedProof: AI-generatedprecheck passaudited 2026-08-29Open item page →

The region under a nonnegative measurable function is product-measurable and has measure equal to the integral

Statement

Let (X,A,μ) be a sigma-finite measure space, let λ1 be Lebesgue measure on R, and let f:X→[0,∞] be measurable. Then

Gf:={(x,t)∈X×R:0≤t<f(x)}

belongs to A⊗L(R) and (μ×λ1)(Gf)=∫Xf dμ.

Facts & Assumptions

Given: A sigma-finite measure space (X,A,μ) and a measurable function f:X→[0,∞].

[L1]

Tonelli's theorem holds for the sigma-finite product X×R. (Tonelli's theorem for nonnegative measurable functions on a sigma-finite product)

Proof

technique · direct
1.1L2

The function (x,t)↦f(x)−t is measurable by [L2], so Gf={(x,t):t≥0}∩{(x,t):f(x)−t>0} is product-measurable.

2.1L1∎

For fixed x, the section of Gf is (Gf)x=[0,f(x)), whose one-dimensional Lebesgue measure is exactly f(x), including the cases f(x)=0 and f(x)=∞. Applying [L1] to 1Gf therefore gives (μ×λ1)(Gf)=∫Xλ1((Gf)x) dμ=∫Xf dμ. This is the claimed area formula.

CorollaryStatement: AI-adaptedProof: AI-generatedprecheck passaudited 2026-08-29Open item page →

The graph of a measurable function R^n to R is Lebesgue null

Statement

Assume the Axiom of Countable Choice (The Axiom of Countable Choice (ACω)). Let n≥1 and let f:Rn→R be Lebesgue measurable. Then its graph Γf:={(x,t)∈Rn×R:t=f(x)} is Lebesgue measurable and has (n+1)-dimensional Lebesgue measure zero.

Facts & Assumptions

Given: The Axiom of Countable Choice, a positive integer n, and a Lebesgue measurable function f:Rn→R.

[L2]
[L3]

Assuming countable choice, countable subsets of Euclidean space are Lebesgue null. (Every at most countable subset of Rn is Lebesgue null; in particular λ1(Q)=0)

Proof

technique · direct
1.1L1

The function H(x,t):=t−f(x) is measurable by [L1], so Γf=H−1({0}) is measurable.

2.1L2L3∎

For each x∈Rn, the section (Γf)x is the singleton {f(x)}, which is countable and therefore Lebesgue null by [L3]. Applying [L2] to 1Γf yields λn+1(Γf)=∫Rnλ1((Γf)x) dλn=∫Rn0 dλn=0. Hence the graph is Lebesgue null.

DefinitionDefinition: AI-adaptedProof: Not applicablejudge pass (gpt-5.6-terra)audited 2026-08-29Open item page →

The distribution function of absolute value

Definition

Let (X,A,μ) be a measure space and let f:X→C be measurable. The distribution function of ∣f∣ is the map Af:[0,∞)→[0,∞] defined by

Af(t):=μ({x∈X:∣f(x)∣>t}).

This is the tail function that appears in the layer-cake formula.

TheoremStatement: AI-adaptedProof: AI-generatedverified 2026-09-26 (gpt-6-sol)Open item page →

For 0 < p < infinity, the layer-cake formula computes the integral of |f|^p from the distribution function

Statement

Let (X,A,μ) be a measure space, let f:X→C be measurable, and let 0<p<∞. Then ∫X∣f∣p dμ=p∫0∞tp−1μ({∣f∣>t}) dt=p∫0∞tp−1Af(t) dt, where either side may be +∞.

Facts & Assumptions

Given: A measurable function f:X→C and a real number 0<p<∞.

[L1]

The distribution function is Af(t)=μ({∣f∣>t}). (The distribution function of absolute value)

[L2]

The derivative of tp is ptp−1 on (0,∞). Thus the fundamental theorem of calculus gives ∫εaptp−1 dt=ap−εp for 0<ε<a. (Continuity and derivatives of positive-base real powers, The second fundamental theorem: if G is differentiable on [a,b] with G′=f and f is integrable, then ∫abf=G(b)−G(a))

[L3]

Every nonnegative measurable function admits increasing simple approximations. (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
1.1L2L4

Fix a≥0. If a=0, both integrals below are zero. If a>0, apply [L2] on [ε,a] and let ε↓0. Since p>0, εp→0; monotone convergence for the nonnegative integrand gives ap=∫0aptp−1 dt=∫0∞ptp−11{t<a} dt. This argument also covers 0<p<1, when tp−1 is unbounded at zero.

2.1step 1.1algebra

Let s=∑j=1maj1Ej be a nonnegative simple function, with the sets Ej pairwise disjoint and the coefficients aj≥0. Then ∫Xsp dμ=∑j=1majpμ(Ej). Using step 1.1 for each coefficient and exchanging the resulting finite sum with the real integral gives ∫Xsp dμ=p∫0∞tp−1μ({s>t}) dt.

3.1L1L3L4step 2.1∎

By [L3], choose simple functions sn↑∣f∣. Then snp↑∣f∣p, and for each t≥0 one has 1{sn>t}↑1{∣f∣>t}, hence μ({sn>t})↑μ({∣f∣>t})=Af(t) by [L1]. Applying [L4] first on X and then on (0,∞) to the identities from step 2.1 yields ∫X∣f∣p dμ=p∫0∞tp−1μ({∣f∣>t}) dt=p∫0∞tp−1Af(t) dt.

DefinitionDefinition: AI-adaptedProof: Not applicableaudited 2026-08-29Open item page →

The polar surface set function on the unit sphere

Definition

Assume the Axiom of Countable Choice (The Axiom of Countable Choice (ACω)). Fix n≥1 and write Sn−1:={ω∈Rn:∣ω∣=1}. Let Φ:Rn∖{0}⟶(0,∞)×Sn−1,Φ(x)=(∣x∣,x/∣x∣). This map is continuous. If E⊆Sn−1 is Borel, then (0,1]×E is Borel and {rω:ω∈E, 0<r≤1}=Φ−1((0,1]×E) is Borel in Rn∖{0} by A continuous map has Borel preimages of Borel sets, hence Borel in Rn by The Borel sigma-algebra of a subspace is the trace of the ambient Borel sigma-algebra. It is therefore Lebesgue measurable by Assuming countable choice, every Borel subset of Rn is Lebesgue measurable. Define σ(E):=n λn({rω:ω∈E, 0<r≤1}).

The next theorem proves that this is a Borel measure on Sn−1 and that it is exactly the surface measure needed for polar coordinates.

TheoremStatement: AI-adaptedProof: AI-generatedverified 2026-09-26 (gpt-6-sol)Open item page →

Polar coordinates decompose Lebesgue measure into r^{n-1} dr d sigma

Statement

Assume the Axiom of Countable Choice (The Axiom of Countable Choice (ACω)). Let n≥1, let Sn−1⊆Rn be the unit sphere, and let σ be the set function of The polar surface set function on the unit sphere. Then σ is a finite Borel measure on Sn−1, and for every Borel measurable f:Rn→[0,∞], ∫Rnf(x) dλn(x)=∫0∞∫Sn−1f(rω)rn−1 dσ(ω) dr. Moreover, σ is the unique Borel measure on Sn−1 with this property.

Facts & Assumptions

Given: The Axiom of Countable Choice, a positive integer n, and a Borel measurable function f:Rn→[0,∞].

[L1]

The set function σ is defined by σ(E)=n λn({rω:ω∈E, 0<r≤1}) for Borel E⊆Sn−1. (The polar surface set function on the unit sphere)

[L3]

Two measures that agree on a sigma-finite generating pi-system agree on the generated sigma-algebra. (Measures agreeing on a generating pi-system are equal under an increasing finite-measure exhaustion from that pi-system)

[L4]

Tonelli's theorem turns equality of measures on sets into the corresponding equality of nonnegative integrals. (Tonelli's theorem for nonnegative measurable functions on a sigma-finite product)

[L5]

Assuming countable choice, bounded subsets of Euclidean space have finite outer measure. (Lebesgue measure is sigma-finite, and every metrically bounded subset of Rn has finite outer measure)

[A1]

Let Φ:Rn∖{0}→(0,∞)×Sn−1 be Φ(x)=(∣x∣,x/∣x∣). This map is continuous, so m∗(B):=λn(Φ−1(B)) defines a measure on the Borel subsets of (0,∞)×Sn−1.

[A2]

Sets of the form (a,b]×E with 0<a<b and Borel E⊆Sn−1 form a sigma-finite generating pi-system for the Borel sigma-algebra of (0,∞)×Sn−1.

Proof

technique · direct
1.1L1L5A1

For Borel E⊆Sn−1 put Er:={sω:ω∈E, 0<s≤r}. By [A1], each Er is Borel. If (Ej) is pairwise disjoint, then the sets (Ej)1 are pairwise disjoint and (⋃jEj)1=⋃j(Ej)1, so countable additivity of λn makes σ a Borel measure. It is finite because σ(Sn−1)=nλn({x:0<∣x∣≤1})<∞ by [L5].

2.1L1L2A1step 1.1

For Borel E⊆Sn−1 and 0<a<b, [L1] gives λn(E1)=σ(E)/n. The dilation x↦rx has determinant rn, so [L2] gives λn(Er)=rnλn(E1)=rnnσ(E). Therefore m∗((a,b]×E)=λn(Eb∖Ea)=bn−annσ(E)=σ(E)∫abrn−1 dr.

3.1A2L3L4step 1.1step 2.1∎

Step 2.1 shows that m∗ and the product measure rn−1dr×σ agree on the generating pi-system of [A2]. The rectangles Pk=(1/k,k]×Sn−1 for k≥2 increase to the whole product and have the same finite measure under both measures, namely σ(Sn−1)(kn−k−n)/n; hence [L3] applies and the measures agree on every Borel subset of (0,∞)×Sn−1. Applying [L4] to this identity gives the integral formula on Rn∖{0}. The omitted origin has Lebesgue measure zero: it lies in a half-open box of volume εn for every ε>0. Thus the same formula holds for every nonnegative Borel measurable f on all of Rn, even when f(0)=+∞. If σ~ is another Borel measure on Sn−1 with the same integral formula, apply that formula to 1E1, where E1={rω:ω∈E, 0<r≤1}. Then λn(E1)=∫0∞∫Sn−11E1(rω)rn−1 dσ~(ω) dr=σ~(E)∫01rn−1 dr=σ~(E)n, so σ~(E)=nλn(E1)=σ(E) by [L1]. Thus σ~=σ, proving uniqueness.

RemarkRemark: AI-adaptedProof: Not applicablejudge pass (gpt-5.6-terra)audited 2026-08-29Open item page →

Polar coordinates recover the published ball-volume and Gaussian formulas

Assuming the Axiom of Countable Choice required by Polar coordinates decompose Lebesgue measure into r^{n-1} dr d sigma, applying the polar formula to radial indicators recovers the published volume formulas The closed form for the volume of the unit n-ball and The volume of a radius-r closed n-ball is πn/2rn/Γ(n/2+1). The cited The plane Gaussian integral equals π by polar coordinates is instead an earlier instance of the same polar method; the present theorem subsumes that two-dimensional calculation rather than providing an independent Gamma-function route to it.

This page records the bridge, not a duplicate proof of those already-published closed forms.

LemmaStatement: AI-adaptedProof: AI-generatedprecheck passverified 2026-09-23 (gpt-6-sol)Open item page →

A C^1 diffeomorphism maps Lebesgue null sets to Lebesgue null sets

Statement

Assume the Axiom of Countable Choice ACω. Let U,V⊆Rn be open and let T:U→V be a C1 diffeomorphism. If N⊆U is Lebesgue null, then T(N) is Lebesgue null.

Facts & Assumptions

Given: Countable Choice, open sets U,V⊆Rn, a C1 diffeomorphism T:U→V, and a Lebesgue null set N⊆U.

[L1]

Lipschitz self-maps of Euclidean space send closed-cube-cover null sets to closed-cube-cover null sets (A Lipschitz map Rm→Rm sends null sets to null sets).

[L2]

Under Countable Choice, a subset of Rn is Lebesgue null exactly when it is null in this closed-cube-cover sense (A subset of Rm has Lebesgue outer measure zero if and only if it is null in the sense of countable closed-cube covers, The Axiom of Countable Choice (ACω)).

[L3]

Lebesgue measure is countably subadditive (Finite and countable subadditivity of measures).

[A1]

The rational closed cubes of positive side length lying in U form a countable family and their interiors cover U (Q is countably infinite). For each such cube Q, continuity of DT bounds its derivative on the compact convex cube, so the mean-value inequality makes T∣Q Lipschitz. The coordinatewise clamp rQ:Rn→Q is 1-Lipschitz; hence SQ=T∘rQ is a global Lipschitz extension agreeing with T on Q. These formulas define the extensions from the cubes without a countable selection.

Proof

technique · direct
1.1A1L1L2

Enumerate the rational cubes of [A1] as (Qj) and write N=⋃j(N∩Qj). By [L2], each N∩Qj is closed-cube-cover null. The global Lipschitz extension SQj from [A1] agrees with T on Qj, so [L1] makes SQj(N∩Qj)=T(N∩Qj) closed-cube-cover null. Applying [L2] again shows that each image is Lebesgue null.

2.1L3step 1.1∎

Since T(N)=⋃jT(N∩Qj), [L3] implies λn(T(N))≤∑jλn(T(N∩Qj))=0. Hence T(N) is Lebesgue null.

LemmaStatement: AI-adaptedProof: AI-generatedprecheck passaudited 2026-08-29Open item page →

A C^1 diffeomorphism maps Lebesgue measurable sets to Lebesgue measurable sets

Statement

Assume the Axiom of Countable Choice (The Axiom of Countable Choice (ACω)). Let U,V⊆Rn be open and let T:U→V be a C1 diffeomorphism. If E⊆U is Lebesgue measurable, then T(E) is Lebesgue measurable.

Facts & Assumptions

Given: The Axiom of Countable Choice, open sets U,V⊆Rn, a C1 diffeomorphism T:U→V, and a Lebesgue measurable set E⊆U.

[L1]

A C1 diffeomorphism maps null sets to null sets. (A C^1 diffeomorphism maps Lebesgue null sets to Lebesgue null sets)

[L2]

Assuming countable choice, every Lebesgue measurable set is a Borel set up to a null modification. (L(Rn) is exactly the completion of the restriction of λn to the Borel sets)

[L3]

Continuous preimages of Borel sets are Borel. (A continuous map has Borel preimages of Borel sets)

Proof

technique · direct
1.1L1L2L3

By [L2], write E=B∪N with B Borel and N contained in a null set. Since T−1 is continuous, [L3] implies that T(B)=(T−1)−1(B) is Borel. Also [L1] makes T(N) null.

2.1step 1.1L2∎

Therefore T(E)=T(B)∪T(N) is a Borel set union a null set, hence Lebesgue measurable by [L2].

LemmaStatement: AI-adaptedProof: AI-generatedprecheck passaudited 2026-08-29Open item page →

The published Riemann change-of-variables theorem already gives the Lebesgue formula for continuous compactly supported integrands

Statement

Let U,V⊆Rn be open and let T:U→V be a C1 diffeomorphism. If f:V→R is continuous and compactly supported, then ∫Vf(y) dλn(y)=∫Uf(T(x)) ∣det⁡DT(x)∣ dλn(x).

Facts & Assumptions

Given: Open sets U,V⊆Rn, a C1 diffeomorphism T:U→V, and a continuous compactly supported function f:V→R.

[L1]

Proof

technique · direct
1.1L1L2

Because f has compact support inside V, there is a compact Jordan set K⊆V containing supp⁡(f). Then f vanishes on V∖K, so both integrals in the statement reduce to integrals over K and T−1(K).

2.1L1L2step 1.1∎

The Riemann theorem [L1] applies on these compact sets, and [L2] identifies those Riemann integrals with the corresponding Lebesgue integrals. Therefore the displayed Lebesgue change-of-variables formula holds.

TheoremStatement: AI-adaptedProof: AI-generatedverified 2026-09-23 (gpt-6-sol)Open item page →

A C^1 diffeomorphism satisfies the change-of-variables formula for nonnegative Lebesgue measurable functions

Statement

Assume the Axiom of Countable Choice (The Axiom of Countable Choice (ACω)). Let U,V⊆Rn be open and let T:U→V be a C1 diffeomorphism. For every nonnegative Lebesgue measurable f:V→[0,∞], ∫Vf(y) dλn(y)=∫Uf(T(x)) ∣det⁡DT(x)∣ dλn(x).

Facts & Assumptions

Given: The Axiom of Countable Choice, open sets U,V⊆Rn, a C1 diffeomorphism T:U→V, and a nonnegative Lebesgue measurable function f:V→[0,∞].

[L2]

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

[L3]

Every nonnegative measurable function admits increasing simple approximations. (Every nonnegative measurable function admits an explicit increasing sequence of simple approximations)

[L5]

Two measures on V agreeing on a generating pi-system with a common increasing finite-mass exhaustion from that system agree on all Borel sets (Measures agreeing on a generating pi-system are equal under an increasing finite-measure exhaustion from that pi-system).

[L6]

The nonnegative integral is additive (Additivity of the nonnegative Lebesgue integral).

Proof

technique · direct
1.1L2L6given

On Borel subsets E of V define ν(E):=∫U1E(T(x))∣det⁡DT(x)∣ dλn(x). This is a measure: the nonnegative Jacobian weight is measurable, inverse images under T take disjoint countable unions to disjoint countable unions, [L6] gives finite additivity, and [L2] passes the increasing finite sums through the integral.

2.1L1L2step 1.1

Let W=V∩R for a bounded open rectangle R with rational endpoints. Write d(y,Wc) for Euclidean distance to the complement and ∥y∥∞ for the maximum coordinate modulus. The functions φj(y)=min⁡{1,max⁡(0,jd(y,Wc)−1)}min⁡{1,max⁡(0,j+1−∥y∥∞)} are continuous, nonnegative and increase pointwise to 1W. Each support is contained in the compact set {d(y,Wc)≥1/j, ∥y∥∞≤j+1}⊂W, so φj∣V has compact support in V. Applying [L1] to each φj and [L2] to the two monotone limits gives ν(W)=λn(W). The empty W is immediate.

3.1L5step 1.1step 2.1

The sets V∩R above form a pi-system generating the Borel sigma-algebra of V. The increasing members Pj=V∩(−j,j)n cover V and satisfy λn(Pj)<∞; step 2.1 gives ν(Pj)=λn(Pj). Hence [L5] makes ν(E)=λn(E) for every Borel E⊆V. This proves the set formula without assuming that an infinite-measure equality class is closed under decreasing intersections.

4.1L2L4step 3.1

Let s=∑j=1mcj1Ej be a nonnegative simple Lebesgue measurable function. By [L4], replace each Ej by a Borel set differing from it only by a null set. The set formula from step 3.1 and null-set invariance in [L4] then give the change-of-variables formula for s.

5.1L2L3step 4.1∎

Choose simple functions sk↑f by [L3]. Step 4.1 applies to each sk, and [L2] lets k→∞ on both sides. This yields the formula for f.

CorollaryStatement: AI-adaptedProof: AI-adaptedprecheck passverified 2026-09-09 (gpt-6-astra)Open item page →

A C^1 diffeomorphism satisfies the change-of-variables formula for L^1 functions

Statement

Assume the Axiom of Countable Choice. Let U,V⊆Rn be open and let T:U→V be a C1 diffeomorphism. If f:V→C belongs to L1(λn), then ∫Vf(y) dλn(y)=∫Uf(T(x)) ∣det⁡DT(x)∣ dλn(x).

Facts & Assumptions

Given: Countable choice, open sets U,V⊆Rn, a C1 diffeomorphism T:U→V, and a function f∈L1(λn).

[L5]
[L2]

Lebesgue measurable sets differ from Borel sets only inside Borel null sets, under countable choice. (L(Rn) is exactly the completion of the restriction of λn to the Borel sets, The Axiom of Countable Choice (ACω))

[L3]

A nonnegative measurable function has zero integral exactly when it vanishes almost everywhere; integrals on measurable null sets vanish. (A nonnegative measurable function has integral 0 exactly when it vanishes almost everywhere, A nonnegative integral over a null set vanishes)

Proof

technique · direct
1.1L1L4given

First identify continuous compact-support Riemann and Lebesgue integrals locally. Extend a continuous compactly supported function on an open set by zero; this is continuous because its support is compact inside that open set. On a bounding closed box it is bounded and Riemann integrable by [L1]. Its lower and upper grid step functions, disjointifying cells along null coordinate faces, have Lebesgue integrals equal to the lower and upper Darboux sums. Their difference tends to zero. After adding a fixed constant to make all functions nonnegative, monotonicity squeezes the Lebesgue integral to the Riemann integral; subtract the constant using finite integrability. Apply this to k∈Cc(V) and (k∘T)∣det⁡DT∣, whose support is contained in the compact preimage of supp⁡k. Riemann substitution [L1] therefore proves the Lebesgue substitution formula for k.

2.1L4L5step 1.1construct

For Borel E⊆V, let α(E)=λn(E) and β(E)=∫T−1(E)J dx, with J=∣det⁡DT∣. These are Borel measures by [L5]. For an open rational box R with compact closure in V, the continuous functions kj(y)=min⁡(1,jdist⁡(y,Rn∖R)) have support in R‾ and increase to 1R. Step 1.1 and monotone convergence give α(R)=β(R)<∞. List all such boxes as (Rj) and set Wj=⋃i≤jRi. They exhaust V; finite inclusion-exclusion, whose terms are finite and are boxes or empty, gives agreement on Wj and Wj∩R for every such box R. Thus the finite measures E↦α(E∩Wj) and E↦β(E∩Wj) agree on the pi-system of these boxes, the empty set and V. This pi-system generates the Borel sets because the boxes form a countable basis of V. The equality class is a lambda-system: equal finite total masses allow complements and countable additivity allows disjoint unions. Apply [L5], then take j→∞, to obtain α=β on all Borel sets. If V is empty there is nothing to prove.

3.1L4step 2.1

The Borel set equality of step 2.1 gives substitution for nonnegative Borel simple functions by finite sums. Explicit increasing dyadic simple approximations and [L4] extend it to all nonnegative Borel functions. This establishes the Borel formula locally without a later-page supplier.

4.1L1L2L3given

Put J=∣det⁡DT∣, continuous and strictly positive since T is a diffeomorphism. If Z⊆V is Borel null, step 3.1 gives ∫U1Z(T(x))J(x) dx=0. By [L3] and positivity of J, the Borel set T−1(Z) is null. Countable choice is used in the Borel construction and the completion interface [L2], not in the finite real/imaginary decomposition below.

5.1L1L2L3step 4.1

For Lebesgue measurable E⊆V, write E=A∪N with A Borel and N⊆Z for Borel null Z, intersecting all sets with V. Then T−1(E) is a Borel set modified inside the Borel null set T−1(Z), hence measurable by [L2]. The indicator functions of E,A and their pullbacks agree off the respective null sets, so [L3] and step 3.1 give λn(E)=∫U1E(T(x))J(x) dx.

6.1L4step 5.1construct

Finite nonnegative sums give substitution for nonnegative simple Lebesgue measurable functions. For any nonnegative measurable h, the explicit simple functions sk=2−k⌊2kmin⁡(h,k)⌋ increase to h. Step 5.1 ensures measurability of their pullbacks, hence of h∘T. By [L4], passing to the increasing limits proves ∫Vh=∫U(h∘T)J.

7.1L4step 6.1algebra∎

Apply step 6.1 first to ∣f∣. It gives ∫U∣f∘T∣J=∫V∣f∣<∞, so the transformed complex function is integrable. Write f=u−v+i(p−q) using the nonnegative positive and negative parts of its real and imaginary parts; each is bounded by ∣f∣. Apply step 6.1 to these four functions and recombine their finite integrals by [L4]. This proves the stated identity.

RemarkRemark: AI-adaptedProof: Not applicableaudited 2026-08-29Open item page →

Finite product measures are the base case for countable product constructions

The finite product construction is the library's base case for later countable product arguments. Associativity of the finite product means one can speak unambiguously about μ1×μ2×μ3, but this page does not infer any Kolmogorov-extension theorem or infinite-product measure from that finite fact alone.

5 · Examples, counterexamples and false statements

None yet.

Sources