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27 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 18 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 AA and BB.

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

AB:=σ({A×B:AA, BB}),

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 AB.

Facts & Assumptions

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

[L1]

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

[L2]

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

[A1]

For rectangles, (A1×B1)(A2×B2)=(A1A2)×(B1B2), and (X×Y)(A×B)=(Ac×Y)(A×Bc).

[A2]

If Rj=Aj×Bj for 1jn, 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
1.1

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.

L1A1
2.1

Let R be the family of finite disjoint unions of measurable rectangles. It contains and X×Y. If E,FR, then [A2] disjointifies the finite union EF into finitely many pairwise disjoint measurable rectangles, so EFR. Likewise EF=EFc belongs to R by step 1.1. Thus R is an algebra.

step 1.1A2
3.1

Every measurable rectangle belongs to R, so [L2] gives AB=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 AB. Therefore σ(R)=AB, and R is an algebra generating the product sigma-algebra.

L2step 2.1
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 EX×Y. For xX and yY, the horizontal and vertical sections of E are

Ex:={yY:(x,y)E},Ey:={xX:(x,y)E}.

If f:X×YZ is a function, its sections are

fx:YZ,fx(y):=f(x,y),fy:XZ,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 EAB, then ExB for every xX and EyA for every yY.

Facts & Assumptions

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

[L1]

The product sigma-algebra AB 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 xX, (A×B)x={B,xA,,xA, and for fixed yY, (A×B)y={A,yB,,yB.

[A2]

For fixed x, ((X×Y)E)x=YEx,(n1En)x=n1(En)x, and the analogous formulas hold for vertical sections.

Proof

technique · direct
1.1

Fix xX and let Mx be the family of sets FX×Y such that FxB. By [A1], every measurable rectangle belongs to Mx. By [A2], Mx is a sigma-algebra on X×Y. Since [L1] says AB is generated by the measurable rectangles, [L2] gives ABMx. Therefore ExB.

A1A2L1L2
2.1

Fix yY and let Ny be the family of sets FX×Y such that FyA. The same argument shows that Ny is a sigma-algebra containing all measurable rectangles, hence all of AB. Therefore EyA. Since x and y were arbitrary, every horizontal and vertical section of E is measurable.

step 1.1L1L2A1A2
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×YR be (AB,B(R))-measurable. Then fx:YR is B-measurable for every xX, and fy:XR is A-measurable for every yY.

Facts & Assumptions

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

[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 UR, fx1(U)=(f1(U))x,(fy)1(U)=(f1(U))y.

Proof

technique · direct
1.1

Fix xX and let G be a generating family for B(R). For each UG, the set f1(U) is product-measurable, so [L2] and [A1] give fx1(U)=(f1(U))xB. By [L1], fx is therefore B-measurable.

L1A1L2
2.1

Fix yY. The same argument gives (fy)1(U)=(f1(U))yA for every generator UG, so [L1] implies that fy is A-measurable. Thus every horizontal and vertical section of f is measurable.

step 1.1A1L1L2
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 EX×Y has measurable horizontal sections Ex for every xX and measurable vertical sections Ey for every yY, then EAB.

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
1.1

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

givenL2
2.1

Suppose for contradiction that E were product-measurable for MM. 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.

L1L3A1step 1.1
PropositionStatement: AI-adaptedProof: AI-generatedprecheck passaudited 2026-08-29Open 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 EAB. Then the functions

xν(Ex),yμ(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 EAB.

[L1]

Finite disjoint unions of measurable rectangles form an algebra that generates AB. (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]
[A1]

Since ν is sigma-finite, there are measurable sets YmY with ν(Ym)< for every m. Likewise there are measurable XnX with μ(Xn)<.

[A2]

If FkF, then (Fk)xFx and ν((Fk)xYm)ν(FxYm) for every x. If FkF, then (Fk)xYmFxYm, and continuity from above on the finite-measure space Ym gives ν((Fk)xYm)ν(FxYm).

Proof

technique · direct
1.1

Fix m1 and let Cm be the family of sets FAB for which xν(FxYm) is A-measurable. If F=A×B is a measurable rectangle, then ν(FxYm)=ν(BYm)1A(x), so FCm. By [A2], Cm is a monotone class. Hence [L1] and [L2] imply that every product-measurable set lies in Cm.

L1L2A1A2
2.1

Applying step 1.1 to the given set E shows that gm(x):=ν(ExYm) is measurable for every m. Because YmY, one has gm(x)ν(Ex) for each x, so [L3] gives measurability of xν(Ex).

A1L3step 1.1
3.1

The same argument with the finite-measure exhaustion XnX shows that yμ(Ey) is measurable. Therefore both section-measure functions are measurable.

A1L3step 1.1step 2.1
TheoremStatement: AI-adaptedProof: AI-generatedprecheck passaudited 2026-08-29Open 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 EAB. Then

Xν(Ex)dμ=Yμ(Ey)dν.

Facts & Assumptions

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

[L1]

The section-measure functions xν(Ex) and yμ(Ey) are measurable. (For sigma-finite measures, the section-measure functions are measurable)

[L2]

Finite disjoint unions of measurable rectangles form an algebra generating AB. (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 XnX and YnY with μ(Xn),ν(Yn)<.

Proof

technique · direct
1.1

Fix n,m1. Let Dn,m be the family of measurable subsets FXn×Ym such that Xnν(Fx)dμ=Ymμ(Fy)dν. If F=(A×B)(Xn×Ym), then Fx=(BYm) for xAXn and otherwise, so both integrals equal μ(AXn)ν(BYm). Finite additivity gives the same equality for the algebra of [L2].

L2L3A1
1.2

If FkF inside Xn×Ym, then [L1] and [L4] give Xnν((Fk)x)dμXnν(Fx)dμ, and similarly on Ym. Thus Dn,m is a monotone class. By [L2] and [L3], every measurable subset of Xn×Ym belongs to Dn,m.

L1L4L2L3
2.1

Put En,m:=E(Xn×Ym). Step 1.2 gives Xnν((En,m)x)dμ=Ymμ((En,m)y)dν. Now (En,m)x=ExYm for xXn and otherwise, so as n,m the two integrands increase pointwise to ν(Ex) and μ(Ey).

step 1.2A1
3.1

Applying [L4] on both sides of step 2.1 and then letting n,m gives Xν(Ex)dμ=Yμ(Ey)dν. This is the claimed equality.

L4step 2.1L1
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 EAB, 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 passaudited 2026-08-29Open 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 AB;
  2. for measurable rectangles, (μ×ν)(A×B)=μ(A)ν(B);
  3. the measure μ×ν is sigma-finite; and
  4. it is the unique measure on AB 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)

[A1]

Measurable rectangles form a pi-system that generates AB.

[A2]

Since μ and ν are sigma-finite, there are measurable exhaustions XnX and YnY with μ(Xn),ν(Yn)<.

Proof

technique · direct
1.1

If E=A×B is a measurable rectangle, then (A×B)x={B,xA,,xA, so (μ×ν)(A×B)=Xν((A×B)x)dμ=Xν(B)1A(x)dμ=μ(A)ν(B). This is the rectangle formula.

L1
1.2

Let E1,E2, be pairwise disjoint measurable subsets of X×Y, and put FN:=kNEk. Then (FN)x=kN(Ek)x is a disjoint union, so ν((FN)x)=kNν((Ek)x) for every x. Therefore (μ×ν)(FN)=XkNν((Ek)x)dμ. Since FNk1Ek, [L2] gives (μ×ν)(k1Ek)=k1(μ×ν)(Ek). Thus μ×ν is a measure.

L1L2
2.1

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.

A2step 1.1
3.1

Let ρ be another measure on AB 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 AB. This proves existence, the rectangle formula, sigma-finiteness, and uniqueness.

A1L3step 1.1step 2.1
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 AB 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)=10=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
1.1

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.

given
2.1

The same witness also satisfies ρ(D)=10=τ(D), so ρτ. Hence the displayed universal uniqueness claim is false. This shows why the sigma-finiteness hypothesis in [L1] is essential.

L1givenstep 1.1
TheoremStatement: AI-adaptedProof: AI-generatedprecheck passaudited 2026-08-29Open 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 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
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
1.1

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].

A1algebra
1.2

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

A2algebra
1.3

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

A2algebra
2.1

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.

L1step 1.1step 1.2step 1.3
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×YC 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×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 function fL1(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 gdηgdη for every integrable function g. (The modulus of an integral is bounded by the integral of the modulus)

Proof

technique · direct
1.1

By [L2], the function f is nonnegative measurable, and [L1] gives X(Yfxdν)dμ=X×Yfd(μ×ν)<. Therefore Yfxdν< for μ-almost every x, so fxL1(ν) for μ-almost every x. The same argument with the variables reversed gives fyL1(μ) for ν-almost every y and shows that the section integrals of f are integrable.

L1L2
2.1

For almost every x from step 1.1, [L4] gives YfxdνYfxdν. Define the section integral to be 0 on the exceptional null set where fxL1(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 yXfydμ.

step 1.1L4
3.1

Write f=uv+i(pq), where u,v,p,q0 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,qf. Applying [L1] to these four nonnegative functions and recombining with [L3] yields the stated equality of the three integrals.

step 1.1step 2.1L1L3
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,AB):

μ×ν:=the completion of μ×ν.

Its sigma-algebra consists of sets that differ from an (AB)-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 passaudited 2026-08-29Open 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, then for μ-almost every x the section fx is B-measurable, for ν-almost every y the section fy is A-measurable, and fdμ×ν=X(Yfxdν)dμ=Y(Xfydμ)dν.
  2. If fL1(μ×ν), the same almost-everywhere section-measurability conclusion holds and the same equality of integrals is valid.

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 fL1(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
1.1

By [L1], choose a product-measurable 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 NZ.

L1choose
1.2

Apply the nonnegative case of [L2] to 1Z. Since [L2] gives (μ×ν)(Z)=0, Tonelli yields Xν(Zx)dμ=0,Yμ(Zy)dν=0. Hence ν(Zx)=0 for μ-almost every x and μ(Zy)=0 for ν-almost every y. Because NxZx and NyZy, the equalities fx=gx and fy=gy fail only on null sections of the completed factor spaces. For such x, the section fx is almost everywhere equal to the measurable section gx, so [L4] makes fx B-measurable; similarly for fy.

L2L4
2.1

In the nonnegative case, apply Tonelli from [L2] to g. Since f=g almost everywhere on the complete product space, the completed integral of f equals that of g, and the section integrals agree for the almost-everywhere parameters isolated in step 1.2. This proves part 1.

L2step 1.2
3.1

If fL1(μ×ν), apply [L1] separately to Ref and Imf. This gives product-measurable real-valued functions u,v such that u=Ref and v=Imf almost everywhere. Put g:=u+iv. Then g is product-measurable, g=f almost everywhere, and [L3] applied to f and g shows gL1(μ×ν). The L1 case of [L2] applies to g, step 1.2 transfers the almost-everywhere section measurability from g to f, and [L3] transfers the equality of integrals from g to f. This proves part 2.

L1L2L3L5step 1.2
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 NR, the set E:={0}×NR2, 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
1.1

For each n1, the rectangle Zn:={0}×[n,n] satisfies (λ×λ)(Zn)=λ({0})λ([n,n])=0 by [L3], so Z:={0}×R=n1Zn is (λ×λ)-null.

L3algebra
2.1

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

L2step 1.1
3.1

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.

L1step 2.1
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,n1. 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+nRm and π2:Rm+nRn are continuous.

[A2]

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

Proof

technique · direct
1.1

If ARm and BRn are Borel, then A×B=π11(A)π21(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).

A1L2
2.1

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.

step 1.1A2L1
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-generatedprecheck passaudited 2026-08-29Open 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,n1. 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)

[L4]

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

[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 in Rm+n form a sigma-finite generating pi-system for B(Rm+n).

Proof

technique · direct
1.1

Let Q=i<m+n(ai,bi] be a rational half-open box. Split it as Q=A×B with ARm and BRn. Then step 2 of [L2] and [L3] give (λm×λn)(Q)=λm(A)λn(B)=i<m+n(biai)=λm+n(Q).

L2L3
2.1

By [L4], both measures are sigma-finite on the pi-system of [A1]. Step 1.1 shows that they agree there, and [L1] identifies the generated sigma-algebra with B(Rm+n). Therefore [L5] implies λm×λn=λm+n on every Borel set.

A1L4L5step 1.1
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,n1. 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
1.1

Let AL(Rm) and BL(Rn). By [L2], choose Borel cores A0,B0 and Borel null hulls Z,W such that AA0Z and BB0W. The slabs Z×Rn and Rm×W are Euclidean null: for example, Z×Rn=k1Z×[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.

L1L2L3L4algebra
2.1

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.

step 1.1L1L2L3L4L5
3.1

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 EL(Rm+n), [L2] gives a Borel C and a Borel null set Z with ECZ. 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].

L1L2L5L6step 2.1
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,AB,μ×ν) is complete.

Facts & Assumptions

Given: Lebesgue measure λ on R, a non-Lebesgue-measurable set NR, the set E:={0}×NR2, 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
1.1

For each n1, the rectangle Zn:={0}×[n,n] satisfies (λ×λ)(Zn)=λ({0})λ([n,n])=0 by [L3], so Z=n1Zn is (λ×λ)-null.

L3algebra
2.1

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

L1step 1.1
3.1

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.

L1L2step 2.1
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,n1, 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 NR, the set E:={0}×NR2, 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
1.1

For each n1, the rectangle Zn:={0}×[n,n] satisfies (λ×λ)(Zn)=λ({0})λ([n,n])=0 by [L3], so Z=n1Zn is (λ×λ)-null.

L3algebra
2.1

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

L1step 1.1
3.1

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].

L1L2step 2.1
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:0t<f(x)}

belongs to AL(R) and

(μ×λ1)(Gf)=Xfdμ.

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
1.1

The function (x,t)f(x)t is measurable by [L2], so Gf={(x,t):t0}{(x,t):f(x)t>0} is product-measurable.

L2
2.1

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=Xfdμ. This is the claimed area formula.

L1
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 n1 and let f:RnR 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:RnR.

[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
1.1

The function H(x,t):=tf(x) is measurable by [L1], so Γf=H1({0}) is measurable.

L1
2.1

For each xRn, 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=Rn0dλn=0. Hence the graph is Lebesgue null.

L2L3
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:XC be measurable. The distribution function of f is the map Af:[0,)[0,] defined by

Af(t):=μ({xX:f(x)>t}).

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

TheoremStatement: AI-adaptedProof: AI-generatedprecheck passaudited 2026-08-29Open 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:XC be measurable, and let 0<p<. Then Xfpdμ=p0tp1μ({f>t})dt=p0tp1Af(t)dt, where either side may be +.

Facts & Assumptions

Given: A measurable function f:XC 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 ptp1 on (0,), and the fundamental theorem of calculus recovers ap by integrating that derivative. (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
1.1

Fix a0. By [L2], ap=0aptp1dt=0ptp11{t<a}dt.

L2
2.1

Let s=j=1maj1Ej be a nonnegative simple function, with the sets Ej pairwise disjoint and the coefficients aj0. Then Xspdμ=j=1majpμ(Ej). Using step 1.1 for each coefficient and exchanging the resulting finite sum with the real integral gives Xspdμ=p0tp1μ({s>t})dt.

step 1.1algebra
3.1

By [L3], choose simple functions snf. Then snpfp, and for each t0 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 Xfpdμ=p0tp1μ({f>t})dt=p0tp1Af(t)dt.

L1L3L4step 2.1
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 n1 and write Sn1:={ωRn:ω=1}. Let Φ:Rn{0}(0,)×Sn1,Φ(x)=(x,x/x). This map is continuous. If ESn1 is Borel, then (0,1]×E is Borel and {rω:ωE, 0<r1}=Φ1((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):=nλn({rω:ωE, 0<r1}).

The next theorem proves that this is a Borel measure on Sn1 and that it is exactly the surface measure needed for polar coordinates.

TheoremStatement: AI-adaptedProof: AI-generatedprecheck passaudited 2026-08-29Open 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 n1, let Sn1Rn 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 Sn1, and for every Borel measurable f:Rn[0,], Rnf(x)dλn(x)=0Sn1f(rω)rn1dσ(ω)dr. Moreover, σ is the unique Borel measure on Sn1 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)=nλn({rω:ωE, 0<r1}) for Borel ESn1. (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,)×Sn1 be Φ(x)=(x,x/x). This map is continuous, so m(B):=λn(Φ1(B)) defines a measure on the Borel subsets of (0,)×Sn1.

[A2]

Sets of the form (a,b]×E with 0<a<b and Borel ESn1 form a sigma-finite generating pi-system for the Borel sigma-algebra of (0,)×Sn1.

Proof

technique · direct
1.1

For Borel ESn1 put Er:={sω:ωE, 0<sr}. 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(Sn1)=nλn({x:0<x1})< by [L5].

L1L5A1
2.1

For Borel ESn1 and 0<a<b, [L1] gives λn(E1)=σ(E)/n. The dilation xrx has determinant rn, so [L2] gives λn(Er)=rnλn(E1)=rnnσ(E). Therefore m((a,b]×E)=λn(EbEa)=bnannσ(E)=σ(E)abrn1dr.

L1L2A1step 1.1
3.1

Step 2.1 shows that m and the product measure rn1dr×σ agree on the generating pi-system of [A2]. Both are sigma-finite there, so [L3] implies that they agree on every Borel subset of (0,)×Sn1. Applying [L4] to this measure identity gives the stated polar-coordinate integral formula for every nonnegative Borel measurable f. If σ~ is another Borel measure on Sn1 with the same integral formula, apply that formula to 1E1, where E1={rω:ωE, 0<r1}. Then λn(E1)=0Sn11E1(rω)rn1dσ~(ω)dr=σ~(E)01rn1dr=σ~(E)n, so σ~(E)=nλn(E1)=σ(E) by [L1]. Thus σ~=σ, proving uniqueness.

A2L3L4step 1.1step 2.1
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 passaudited 2026-08-29Open item page →

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

Statement

Let U,VRn be open and let T:UV be a C1 diffeomorphism. If NU is Lebesgue null, then T(N) is Lebesgue null.

Facts & Assumptions

Given: Open sets U,VRn, a C1 diffeomorphism T:UV, and a null set NU.

[L1]

Lipschitz self-maps of Euclidean space send null sets to null sets. (A Lipschitz map RmRm sends null sets to null sets)

[L2]

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

[A1]

There are closed cubes QjU with jQj=U such that for each j there is a Lipschitz map Sj:RnRn agreeing with T on Qj. This is the standard cube-and-clamp construction: choose an open cube whose closure still lies in U, use continuity of DT there to get a derivative bound and hence a Lipschitz bound on that cube, then compose T with the coordinatewise clamp onto the cube to obtain a global Lipschitz extension.

Proof

technique · direct
1.1

Write N=j1(NQj) using [A1]. Each set NQj is null, and the global Lipschitz extension Sj from [A1] agrees with T on Qj. Therefore [L1] gives λn(T(NQj))=λn(Sj(NQj))=0 for every j.

A1L1
2.1

Since T(N)=j1T(NQj), [L2] implies λn(T(N))j1λn(T(NKj))=0. Hence T(N) is Lebesgue null.

L2step 1.1
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,VRn be open and let T:UV be a C1 diffeomorphism. If EU is Lebesgue measurable, then T(E) is Lebesgue measurable.

Facts & Assumptions

Given: The Axiom of Countable Choice, open sets U,VRn, a C1 diffeomorphism T:UV, and a Lebesgue measurable set EU.

[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
1.1

By [L2], write E=BN with B Borel and N contained in a null set. Since T1 is continuous, [L3] implies that T(B)=(T1)1(B) is Borel. Also [L1] makes T(N) null.

L1L2L3
2.1

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

step 1.1L2
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,VRn be open and let T:UV be a C1 diffeomorphism. If f:VR is continuous and compactly supported, then

Vf(y)dλn(y)=Uf(T(x))detDT(x)dλn(x).

Facts & Assumptions

Given: Open sets U,VRn, a C1 diffeomorphism T:UV, and a continuous compactly supported function f:VR.

[L1]

Proof

technique · direct
1.1

Because f has compact support inside V, there is a compact Jordan set KV containing supp(f). Then f vanishes on VK, so both integrals in the statement reduce to integrals over K and T1(K).

L1L2
2.1

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.

L1L2step 1.1
TheoremStatement: AI-adaptedProof: AI-generatedprecheck passaudited 2026-08-29Open 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,VRn be open and let T:UV be a C1 diffeomorphism. For every nonnegative Lebesgue measurable f:V[0,],

Vf(y)dλn(y)=Uf(T(x))detDT(x)dλn(x).

Facts & Assumptions

Given: The Axiom of Countable Choice, open sets U,VRn, a C1 diffeomorphism T:UV, 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)

[A1]

The class of Borel sets EV for which λn(E)=U1E(T(x))detDT(x)dλn(x) is a monotone class containing the open rectangles of V.

Proof

technique · direct
1.1

By [L1], the change-of-variables formula holds for continuous compactly supported functions. Approximating indicators of open rectangles from below by such functions and using [L2] shows that the set formula of [A1] holds for open rectangles. Because the class in [A1] is a monotone class, the monotone class theorem extends the set formula to all Borel sets in V.

L1L2
2.1

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 1.1 and null-set invariance in [L4] then give the change-of-variables formula for s.

L2L4
3.1

Choose simple functions skf by [L3]. Step 2.1 applies to each sk, and [L2] lets k on both sides. This yields the formula for f.

L2L3step 2.1
CorollaryStatement: AI-adaptedProof: AI-generatedprecheck passaudited 2026-08-29Open item page →

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

Statement

Let U,VRn be open and let T:UV be a C1 diffeomorphism. If f:VC belongs to L1(λn), then

Vf(y)dλn(y)=Uf(T(x))detDT(x)dλn(x).

Facts & Assumptions

Given: Open sets U,VRn, a C1 diffeomorphism T:UV, and a function fL1(λn).

[L1]

The change-of-variables formula holds for nonnegative measurable functions. (A C^1 diffeomorphism satisfies the change-of-variables formula for nonnegative Lebesgue measurable functions)

[L2]

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

Proof

technique · direct
1.1

Write f=uv+i(pq), where u,v,p,q0 are the positive and negative parts of the real and imaginary parts of f. Since fL1, all four functions are integrable and nonnegative.

L1L2
2.1

Apply [L1] to u,v,p,q and recombine the four resulting equalities by [L2]. This yields the stated formula for f.

step 1.1L1L2
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