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The Lebesgue Integral and the Convergence Theorems

1 · Prerequisites

2 · Summary

This page builds the Lebesgue integral in the three-stage route fixed by the measure-theory design notes. First come nonnegative simple functions and the simple integral, then the nonnegative integral together with monotone convergence, Fatou, and the density construction, and only after that the signed and complex theories.

The page's false statements record the exact hypotheses the convergence theorems spend: monotonicity for monotone convergence, a dominating integrable majorant for dominated convergence, almost-everywhere rather than everywhere equality for zero-integral criteria, and probability normalization for Jensen's inequality.

3 · Logical flowchart

4 · Definitions, theorems and proofs

DefinitionDefinition: Literature-sourcedProof: Not applicablejudge pass (gpt-5.6-terra)audited 2026-08-27Open item page →

Extended-real-valued measurable functions

Definition

Let (X,A,μ) be a measure space (Measure spaces). Equip R‾ (The extended real line R‾=R∪{−∞,+∞}, its order, and the arithmetic that is left undefined) with its order topology and let B(R‾) be the corresponding Borel sigma-algebra (The Borel sigma-algebra of a topological space).

A function f:X→R‾ is measurable when f−1(B)∈A for every B∈B(R‾).

Equivalently, it is enough to require {x∈X:f(x)>a}∈Afor every a∈R, because the rays (a,+∞] generate B(R‾).

DefinitionDefinition: Literature-sourcedProof: Not applicablejudge pass (gpt-5.6-terra)audited 2026-08-27Open item page →

Nonnegative simple measurable functions

Definition

Let (X,A,μ) be a measure space. A measurable function s:X→[0,+∞)⊆R‾ (Extended-real-valued measurable functions) is a nonnegative simple measurable function when it has finite range.

Equivalently, there are pairwise disjoint measurable sets E1,…,Em∈A and coefficients c1,…,cm∈[0,+∞) such that s=∑j=1mcjχEj. Any such display is a simple representation of s.

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

Closure properties of measurable functions used by the integral

Statement

Let (X,A,μ) be a measure space.

  1. If f,g:X→R‾ are measurable and f+g is defined pointwise, then f+g is measurable.
  2. If c∈R and f:X→R is measurable, then cf is measurable.
  3. If f:X→R is measurable, then f+=max⁡{f,0}, f−=max⁡{−f,0}, and ∣f∣=f++f− are measurable.
  4. If E∈A and f:X→[0,+∞] is measurable, then fχE is measurable, where this function equals f on E and 0 off E (in particular, 0⋅(+∞)=0 here).
  5. If (fn) is a sequence of measurable functions X→R‾, then inf⁡nfn is measurable; if moreover fn↑f pointwise, then f is measurable.

Facts & Assumptions

Given: A measure space (X,A,μ) and functions or sets as in the relevant clause.

[L1]

A function h:X→R‾ is measurable exactly when {h>a}∈A for every real a (Extended-real-valued measurable functions).

[L2]

A sigma-algebra contains X and ∅ and is closed under complements and countable unions; countable intersections follow by taking complements (Sigma-algebras).

Proof

technique · direct
1.1L1L2L3

For any extended-real-valued h, the identities {h<a}=⋃q∈Q, q<a(X∖{h>q}) and {h>a}=⋃q∈Q, q>a(X∖{h<q}) follow from rational density, including when h(x) is infinite. Thus [L2] and [L3] show that measurability of all strict sublevels is equivalent to measurability of all strict superlevels.

1.2givenL1L2

Put h=fχE as defined in clause 4. For a<0, {h>a}=X, since h≥0. For a≥0, {h>a}=E∩{f>a}. Both sets are measurable, including at a=0, so clause 4 follows.

1.3L1L2L3given

For a pointwise-defined sum, {f+g>a}=⋃q∈Q({f>q}∩{g>a−q}). Indeed, if both summands are finite and their sum exceeds a, choose a rational strictly between a−g(x) and f(x). If one summand is +∞, the other is not −∞, and a rational meeting the two inequalities still exists; if a summand is −∞, the defined sum cannot exceed a. The reverse inclusion follows by adding the inequalities. The union is countable and measurable, proving clause 1.

2.1L1L2step 1.1

For c>0, {cf>a}={f>a/c}; for c<0, {cf>a}={f<a/c}. If c=0, each superlevel is either X or ∅. Step 1.1 and [L1] therefore prove clause 2.

2.2givenL1L2step 1.1

Put u=inf⁡nfn and v=sup⁡nfn. The defining order properties of infimum and supremum give {u<a}=⋃n{fn<a} and {v>a}=⋃n{fn>a}, including infinite values. By step 1.1 and [L2] these sets are measurable, so u and v are measurable by [L1]. If fn↑f, then f=v pointwise. This proves clause 5.

3.1L1L2step 1.3step 2.1

The function −f is measurable by step 2.1. For any real-valued measurable h, the superlevel of max⁡(h,0) is X when a<0 and {h>a} when a≥0. Apply this to h=f and h=−f to obtain measurable f+ and f−. They are finite-valued, so step 1.3 makes ∣f∣=f++f− measurable, proving clause 3.

4.1step 1.3step 2.1step 3.1step 1.2step 2.2∎

Clauses 1–5 follow respectively from steps 1.3, 2.1, 3.1, 1.2, and 2.2.

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

Every nonnegative measurable function is the increasing limit of simple measurable functions

Statement

Let f:X→[0,+∞] be measurable. Then there is an increasing sequence of nonnegative simple measurable functions (sn) such that sn(x)↑f(x) for every x∈X.

Facts & Assumptions

Given: A measurable function f:X→[0,+∞].

[L1]

For a measurable f, the sets f−1(B) are measurable for every Borel B⊆R‾ (Extended-real-valued measurable functions).

[L2]

A nonnegative measurable function with finite range is a nonnegative simple measurable function (Nonnegative simple measurable functions).

[L3]

Increasing pointwise suprema of measurable functions are measurable, and measurable functions remain measurable under the elementary truncations used below (Closure properties of measurable functions used by the integral).

Proof

technique · direct
1.1L1L2construct

Set s0:=0. For n≥1 and 0≤k<n2n, put En,k:={x:k2−n≤f(x)<(k+1)2−n} and set sn:=∑k=0n2n−1k2−nχEn,k+nχ{f≥n}. Each En,k and {f≥n} is measurable by [L1], the range of sn is finite, and therefore each sn is simple by [L2]; s0 is also simple.

2.1step 1.1algebra

For each x, one has 0≤sn(x)≤f(x). If f(x)<+∞ and n>f(x), then f(x)−2−n<sn(x)≤f(x); if f(x)=+∞, then sn(x)=n. Hence sn(x)→f(x).

3.1step 1.1step 2.1algebra∎

The functions are increasing. Indeed, sn(x) is the largest multiple of 2−n at most f(x)∧n, hence is also a multiple of 2−(n+1) at most f(x)∧(n+1). The maximality of the latter dyadic truncation gives sn(x)≤sn+1(x). Together with step 2.1, this proves sn↑f.

DefinitionDefinition: Literature-sourcedProof: Not applicablejudge pass (gpt-5.6-terra)audited 2026-08-27Open item page →

The integral of a nonnegative simple function

Definition

Let s=∑j=1mcjχEj be a simple representation of a nonnegative simple measurable function (Nonnegative simple measurable functions) on a measure space (X,A,μ), so the Ej∈A are pairwise disjoint and cj≥0. Its simple integral is ∫s dμ:=∑j=1mcjμ(Ej), where μ is the given measure (Measures on sigma-algebras) and the convention 0⋅(+∞)=0 is fixed once and for all.

The next lemma proves that this value is independent of the chosen simple representation.

LemmaStatement: Literature-sourcedProof: AI-generatedprecheck passaudited 2026-08-27Open item page →

The simple integral is independent of the chosen representation

Statement

If a nonnegative simple measurable function s admits two representations s=∑i=1mciχEi=∑j=1ndjχFj, then the two coefficient sums defining ∫s dμ are equal. So The integral of a nonnegative simple function is well defined.

Facts & Assumptions

Given: Two simple representations of the same nonnegative simple measurable function s.

[L1]

The simple integral is defined by ∫s dμ=∑cjμ(Ej) with the convention 0⋅(+∞)=0 (The integral of a nonnegative simple function).

[L2]

A measure is countably additive on pairwise disjoint measurable families, hence finitely additive on finite measurable partitions (Measures on sigma-algebras).

Proof

technique · direct
1.1givenL1

Complete both representations to partitions of X. [given, L1] Put E0=X∖⋃i=1mEi and F0=X∖⋃j=1nFj, with coefficients c0=d0=0. Both are measurable. Adding these zero terms leaves the represented function and each coefficient sum unchanged, including when a complement has infinite measure, by the convention in [L1]. The augmented families (Ei)i=0m and (Fj)j=0n are finite measurable partitions of X.

2.1step 1.1

Refine the two partitions by their intersections. [step 1.1] For 0≤i≤m and 0≤j≤n set Gij=Ei∩Fj. These sets are measurable and pairwise disjoint, and Ei=⨆j=0nGij,Fj=⨆i=0mGij. On every nonempty Gij the two formulas give the same value of s, so ci=dj.

3.1L1L2step 2.1

Apply finite additivity and the nonnegative extended-real finite-sum rules. [L1, L2, step 2.1] They give ∑i=0mciμ(Ei)=∑i=0m∑j=0nciμ(Gij)=∑i=0m∑j=0ndjμ(Gij)=∑j=0ndjμ(Fj). For a zero coefficient, every product with an infinite measure is 0 by [L1]; for a positive coefficient the usual extended-real distributivity applies. Thus no subtraction of infinities occurs.

4.1step 1.1step 3.1∎

Removing the added zero terms from step 3.1 proves equality of the original coefficient sums.

PropositionStatement: Literature-sourcedProof: AI-generatedprecheck passjudge pass (gpt-5.6-terra)audited 2026-08-27Open item page →

The simple integral is monotone, homogeneous, and additive

Statement

Let s,t be nonnegative simple measurable functions and let c≥0.

  1. If s≤t pointwise, then ∫s dμ≤∫t dμ.
  2. If c>0, then ∫cs dμ=c∫s dμ. If c=0, then ∫0s dμ=0. The second clause avoids forming the globally undefined extended-real product 0⋅(+∞).
  3. ∫(s+t) dμ=∫s dμ+∫t dμ.

Facts & Assumptions

Given: Nonnegative simple measurable functions s,t and a scalar c≥0.

[L1]

The simple integral is well defined, so any convenient common refinement of the chosen simple representations may be used to compute it (The simple integral is independent of the chosen representation).

[L2]

The simple integral of ∑jajχEj is ∑jajμ(Ej) with 0⋅(+∞)=0 (The integral of a nonnegative simple function).

Proof

technique · direct
1.1L1construct

Complete the representations of s and t with their zero-valued complements. Take their finite measurable common refinement (Er). On each cell write s=ar and t=br. If s≤t, then ar≤br.

1.2L2

The zero-scalar case is separate. [L2] When c=0, the function cs is zero. Representing it by 0χX gives ∫0s dμ=0, even if μ(X)=+∞, by the definition's local zero-times-infinity convention.

2.1step 1.1L2

Monotonicity follows cell by cell. [step 1.1, L2] On the common partition, ∫s dμ=∑rarμ(Er),∫t dμ=∑rbrμ(Er). For finite or infinite μ(Er), the local simple-integral convention makes arμ(Er)≤brμ(Er) whenever 0≤ar≤br. Summing these nonnegative extended-real inequalities proves clause 1.

2.2step 1.1L2

Additivity follows on the same partition. [step 1.1, L2] The coefficient of s+t on Er is ar+br, and (ar+br)μ(Er)=arμ(Er)+brμ(Er) under the local zero-times-infinity convention. Finite sums in [0,+∞] can be regrouped without subtraction, so clause 3 follows.

3.1step 1.1L2∎

For c>0, scalar multiplication holds cell by cell. [step 1.1, L2] The identity (car)μ(Er)=c(arμ(Er)) is valid in [0,+∞] for positive c, and finite summation gives ∫cs dμ=c∫s dμ. Together with the preceding cases, this proves all three clauses.

DefinitionDefinition: Literature-sourcedProof: Not applicableaudited 2026-08-27Open item page →

The nonnegative Lebesgue integral

Definition

Let f:X→[0,+∞] be measurable (Extended-real-valued measurable functions). Its nonnegative Lebesgue integral is ∫f dμ:=sup⁡{∫s dμ: s is nonnegative simple and 0≤s≤f}, where the simple integral on the right is the one from The integral of a nonnegative simple function.

The set of admissible simple minorants is nonempty because it contains the zero function, which is simple (Nonnegative simple measurable functions).

PropositionStatement: Literature-sourcedProof: AI-generatedprecheck passverified 2026-09-23 (gpt-6-sol)Open item page →

The nonnegative integral agrees with the simple integral on simple functions

Statement

If s is a nonnegative simple measurable function, then its nonnegative Lebesgue integral equals its simple integral: ∫s dμ=∫simples dμ.

Facts & Assumptions

Given: A nonnegative simple measurable function s.

[L1]

The nonnegative integral is the supremum of the simple integrals of all simple minorants 0≤u≤s (The nonnegative Lebesgue integral).

[L2]

The simple integral is monotone on nonnegative simple functions (The simple integral is monotone, homogeneous, and additive).

[L3]

The simple integral itself is well defined on every nonnegative simple function (The integral of a nonnegative simple function, The simple integral is independent of the chosen representation).

Proof

technique · direct
1.1givenL1L3

The function s is one of its own admissible simple minorants, so [L1] gives ∫s dμ≥∫simples dμ.

1.2L1L2L3

If u is any admissible simple minorant of s, then u≤s, so [L2] gives ∫simpleu dμ≤∫simples dμ. Taking the supremum over all such u in [L1] yields the reverse inequality.

2.1step 1.1step 1.2∎

The two inequalities from steps 1.1 and 1.2 give equality of the nonnegative and simple integrals on s.

DefinitionDefinition: Literature-sourcedProof: Not applicablejudge pass (gpt-5.6-terra)audited 2026-08-27Open item page →

Integral over a measurable subset

Definition

Let (X,A,μ) be a measure space, let f:X→[0,+∞] be measurable, and let E∈A. Since Closure properties of measurable functions used by the integral implies that fχE is measurable, define the integral of f over E by ∫Ef dμ:=∫fχE dμ, where the integral on the right is the nonnegative Lebesgue integral of The nonnegative Lebesgue integral.

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

The indefinite integral of a nonnegative simple function is a measure

Statement

Let s be a nonnegative simple measurable function on (X,A,μ) and define νs(A):=∫As dμ(A∈A). Then νs is a measure on (X,A).

Facts & Assumptions

Given: A nonnegative simple measurable function s on (X,A,μ).

[L1]

For measurable A, the set function A↦∫As dμ is defined as A↦∫sχA dμ (Integral over a measurable subset).

[L2]

The simple integral is additive and homogeneous on nonnegative simple functions (The simple integral is monotone, homogeneous, and additive).

[L4]

The integral is independent of the chosen finite measurable representation, so a disjoint partition including the zero-valued complement may be used (The simple integral is independent of the chosen representation).

[L3]

A measure is a set function with value 0 at the empty set and countable additivity on pairwise disjoint measurable families (Measures on sigma-algebras).

Proof

technique · direct
1.1L1L2L4givenalgebra

By [L4], choose a finite measurable partition X=⨆j=0mEj on which s=cj≥0, including its zero-valued complement. For every measurable A, the sets A∩Ej partition A, so [L1] and [L2] give νs(A)=∑j=0mcjμ(A∩Ej). A term with cj=0 is defined to be zero even when μ(A∩Ej)=+∞.

2.1step 1.1L2L3algebra

Step 1.1 gives νs(∅)=0. If (An) is pairwise disjoint, then for each fixed j, the sets (An∩Ej) are pairwise disjoint. Countable additivity of μ and interchange of one finite sum with a nonnegative series give νs(⋃nAn)=∑j=0mcj∑nμ(An∩Ej)=∑n∑j=0mcjμ(An∩Ej)=∑nνs(An). Zero-coefficient terms remain zero by the simple-integral convention.

3.1step 2.1L3∎

Therefore νs satisfies the two conditions in [L3], so it is a measure.

PropositionStatement: Literature-sourcedProof: AI-generatedprecheck passaudited 2026-08-27Open item page →

Monotonicity and nonnegative homogeneity of the nonnegative integral

Statement

Let f,g:X→[0,+∞] be measurable and let c≥0.

  1. If f≤g, then ∫f dμ≤∫g dμ.
  2. If c>0, then ∫cf dμ=c∫f dμ. For c=0, the integral of the zero function is 0. Neither clause forms the undefined extended-real product 0⋅(+∞).

Facts & Assumptions

Given: Nonnegative measurable functions f,g and a scalar c≥0.

[L1]

The nonnegative integral is the supremum of simple minorants (The nonnegative Lebesgue integral).

[L2]

On simple functions, the nonnegative and simple integrals agree (The nonnegative integral agrees with the simple integral on simple functions).

[L3]

The simple integral is homogeneous for positive scalars and has zero integral on the zero simple function (The simple integral is monotone, homogeneous, and additive).

Proof

technique · direct
1.1L1given

If f≤g, every simple minorant of f is also a simple minorant of g. Taking suprema in [L1] gives ∫f dμ≤∫g dμ.

1.2L1L2L3

The zero function has just one nonnegative simple minorant: itself. [L1, L2, L3] Its simple integral is 0 by [L3], so [L1] gives integral 0 for the zero function, even on a space of infinite measure.

2.1L1givenalgebraL2L3∎

For c>0, multiplication by c bijects simple minorants of f with those of cf. The inverse divides by c and preserves nonnegativity and simplicity. By [L2] and [L3], the corresponding simple integrals differ by the factor c. Multiplication by a positive finite real commutes with the supremum in [0,+∞], including when that supremum is infinite. Hence ∫cf dμ=c∫f dμ. Together with steps 1.1 and 1.2, this proves both clauses.

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

Monotone convergence for the integral

Statement

Let 0≤f1≤f2≤⋯ be measurable and suppose fn(x)↑f(x) for every x. Then ∫fn dμ↑∫f dμ.

Facts & Assumptions

Given: A nondecreasing sequence (fn) of nonnegative measurable functions with pointwise limit f.

[L2]

For a nonnegative simple function s, the set function A↦∫As dμ is a measure (The indefinite integral of a nonnegative simple function is a measure).

[L3]

Measures are continuous from below on increasing measurable sets (Continuity from below for measures).

[L4]

The nonnegative integral agrees with the simple integral on simple functions, and the latter is homogeneous on nonnegative simple functions (The nonnegative integral agrees with the simple integral on simple functions, The simple integral is monotone, homogeneous, and additive).

Proof

technique · direct
1.1givenL1

By [L1], the integrals ∫fn dμ increase and are bounded above by ∫f dμ. Write L=sup⁡n∫fn dμ, so L≤∫f dμ in [0,+∞].

1.2givenL2L3

Fix a finite-valued nonnegative simple function s≤f and 0<c<1. Set An={fn≥cs}. The sets An increase to X: where s=0 membership is automatic, and where s>0, the limit f≥s>cs eventually forces fn≥cs. Since A↦∫As dμ is a measure [L2], continuity from below [L3] gives ∫Ans dμ↑∫s dμ.

2.1step 1.2L1L4algebra

On An, cs≤fn, hence csχAn≤fn everywhere. By monotonicity [L1] and simple-integral agreement and homogeneity [L4], c∫Ans dμ≤∫fn dμ≤L. Letting n→∞ in step 1.2 yields c∫s dμ≤L. Letting a fixed sequence cm↑1 shows ∫s dμ≤L, also when the simple integral is infinite.

3.1step 1.1step 2.1∎

The inequality from step 2.1 holds for every admissible simple minorant s≤f. Taking their supremum, as in The nonnegative Lebesgue integral, gives ∫f dμ≤L. Combine this with step 1.1 to obtain ∫fn dμ↑∫f dμ.

CorollaryStatement: Literature-sourcedProof: AI-generatedprecheck passverified 2026-09-23 (gpt-6-sol)Open item page →

Additivity of the nonnegative Lebesgue integral

Statement

If f,g:X→[0,+∞] are measurable, then ∫(f+g) dμ=∫f dμ+∫g dμ.

Facts & Assumptions

Given: Nonnegative measurable functions f and g.

[L1]

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

[L2]

The sum of two measurable nonnegative functions is measurable, and pointwise increasing limits stay measurable (Closure properties of measurable functions used by the integral).

[L3]

Monotone convergence holds for the nonnegative integral (Monotone convergence for the integral).

[L4]

On simple functions, the nonnegative integral agrees with the simple integral, and the latter is additive (The nonnegative integral agrees with the simple integral on simple functions, The simple integral is monotone, homogeneous, and additive).

Proof

technique · direct
1.1L1L2construct

Choose simple functions sn↑f and tn↑g by [L1]. Then sn+tn is simple for each n, and sn+tn↑f+g by [L2].

2.1step 1.1L3L4algebra∎

By [L3] and [L4], ∫(f+g) dμ=lim⁡n∫(sn+tn) dμ=lim⁡n(∫sn dμ+∫tn dμ)=∫f dμ+∫g dμ. The last limit equality also holds when either limiting integral is infinite because addition is continuous for increasing sequences in [0,∞].

CorollaryStatement: Literature-sourcedProof: AI-generatedprecheck passjudge pass (gpt-5.6-terra)audited 2026-08-27Open item page →

Beppo Levi's theorem for nonnegative series

Statement

Let (fk) be nonnegative measurable functions and let Sn:=∑k<nfk,S:=∑k=0∞fk. Then ∫S dμ=∑k=0∞∫fk dμ.

Facts & Assumptions

Given: A sequence (fk) of nonnegative measurable functions.

[L1]

Measurable nonnegative functions are closed under finite sums and increasing pointwise suprema (Closure properties of measurable functions used by the integral).

[L2]

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

[L3]

Monotone convergence holds for the nonnegative integral (Monotone convergence for the integral).

Proof

technique · direct
1.1

Each partial sum Sn is measurable by [L1], the sequence (Sn) is [L1, given] increasing, and Sn↑S pointwise.

2.1

By [L2], ∫Sn dμ=∑k<n∫fk dμ for every n. Applying [step 1.1, L2, L3, algebra] ∎ [L3] to step 1.1 gives ∫S dμ=lim⁡n∫Sn dμ=lim⁡n∑k<n∫fk dμ, which is exactly the displayed series identity.

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

The indefinite integral of a nonnegative measurable function is a measure

Statement

Let f:X→[0,+∞] be measurable and define νf(A):=∫Af dμ(A∈A). Then νf is a measure on (X,A).

Facts & Assumptions

Given: A nonnegative measurable function f.

[L1]

The set function A↦∫Af dμ is defined by A↦∫fχA dμ (Integral over a measurable subset).

[L2]

Monotone convergence holds for the nonnegative integral (Monotone convergence for the integral).

[L3]

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

[L4]

A measure must vanish at the empty set and be countably additive on disjoint measurable sequences (Measures on sigma-algebras).

Proof

technique · direct
1.1L1L2given

One has νf(∅)=0. If (An) is a pairwise disjoint sequence, put Bn:=⋃k<nAk. Then χBn↑χ⋃kAk, so fχBn↑fχ⋃kAk, including where f=+∞ under the convention 0⋅∞=0. By [L2], νf(⋃kAk)=lim⁡nνf(Bn).

2.1step 1.1L3algebra

Because the sets Ak are disjoint, fχBn=∑k<nfχAk. Repeated use of [L3] gives νf(Bn)=∑k<nνf(Ak). Taking the increasing limit in step 1.1 proves countable additivity.

3.1step 1.1step 2.1L4∎

Steps 1.1 and 2.1 verify the two conditions in [L4], so νf is a measure.

DefinitionDefinition: Literature-sourcedProof: Not applicablejudge pass (gpt-5.6-terra)audited 2026-08-27Open item page →

The measure with density f relative to μ

Definition

Let (X,A,μ) be a measure space and let f:X→[0,+∞] be measurable. The measure with density f relative to μ is the measure f dμ:A→[0,+∞],(f dμ)(A):=∫Af dμ, whose measure property is supplied by The indefinite integral of a nonnegative measurable function is a measure.

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

Integrating against a density agrees with integrating the product

Statement

Let f,g:X→[0,+∞] be measurable. Then ∫g d(f dμ)=∫gf dμ.

Facts & Assumptions

Given: Nonnegative measurable functions f and g.

[L1]

The density measure is defined by (f dμ)(A)=∫Af dμ (The measure with density f relative to μ).

[L2]

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

[L3]

Nonnegative measurable functions admit increasing simple approximations, and products with simple functions are measurable by finite sums of indicator products (Every nonnegative measurable function is the increasing limit of simple measurable functions, Closure properties of measurable functions used by the integral).

[L4]

Monotone convergence holds for the nonnegative integral (Monotone convergence for the integral).

[L5]

The nonnegative integral is homogeneous, and on simple functions it agrees with the simple integral for any measure. (Monotonicity and nonnegative homogeneity of the nonnegative integral, The nonnegative integral agrees with the simple integral on simple functions)

Proof

technique · direct
1.1L1L2L5givenalgebra

Suppose first that g=∑j=1mcjχEj is simple with pairwise disjoint measurable Ej. By [L5] for the measure f dμ and then [L1], ∫g d(f dμ)=∑jcj(f dμ)(Ej)=∑jcj∫Ejf dμ. Also gf=∑jcjfχEj has pairwise disjoint summand supports, so [L2] and [L5] give ∫gf dμ=∑jcj∫Ejf dμ. Hence ∫g d(f dμ)=∫gf dμ.

2.1step 1.1L3L4∎

For general measurable g≥0, choose simple gn↑g by [L3]. Then gnf↑gf pointwise (using 0⋅∞=0). Applying [L4] to both measures and step 1.1 to each gn yields ∫g d(f dμ)=lim⁡n∫gn d(f dμ)=lim⁡n∫gnf dμ=∫gf dμ.

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

Fatou's lemma

Statement

Let (fn) be nonnegative measurable functions. Then ∫lim inf⁡n→∞fn dμ≤lim inf⁡n→∞∫fn dμ.

Facts & Assumptions

Given: A sequence (fn) of nonnegative measurable functions.

[L1]

Countable infima of measurable extended-real-valued functions are measurable, and monotone pointwise suprema are measurable (Closure properties of measurable functions used by the integral).

[L2]

Monotone convergence holds for the nonnegative integral (Monotone convergence for the integral).

Proof

technique · direct
1.1L1givenconstruct

For each n, define gn:=inf⁡k≥nfk. Then each gn is measurable by [L1], one has gn≤gn+1 and gn↑lim inf⁡nfn pointwise. Also gn≤fn for every n.

2.1step 1.1L2L3∎

By [L2] and step 1.1, ∫lim inf⁡nfn dμ=lim⁡n∫gn dμ. For every fixed n and all k≥n, one has gn≤gk≤fk. By [L3], ∫gn dμ≤inf⁡k≥n∫fk dμ. Taking the supremum over n and using monotone convergence on the left gives ∫lim inf⁡nfn dμ≤lim inf⁡n∫fn dμ, including infinite values.

CorollaryStatement: Literature-sourcedProof: AI-generatedprecheck passaudited 2026-08-27Open item page →

Reverse Fatou's lemma under an integrable majorant

Statement

Let (fn) be nonnegative measurable functions and let g be a nonnegative measurable function with ∫g dμ<+∞ and fn≤g for every n. Then lim sup⁡n→∞∫fn dμ≤∫lim sup⁡n→∞fn dμ.

Facts & Assumptions

Given: Nonnegative measurable functions fn dominated by a nonnegative measurable function g with finite integral.

[L1]

Fatou's lemma applies to every sequence of nonnegative measurable functions (Fatou's lemma).

[L2]

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

[L4]

Truncations of nonnegative measurable functions and pointwise limsups of measurable sequences are measurable (Closure properties of measurable functions used by the integral).

[L5]

Monotone convergence holds for the nonnegative integral (Monotone convergence for the integral).

Proof

technique · direct
1.1L4givenconstruct

For each m≥1, put gm:=g∧m and un,m:=fn∧m. Then gm and un,m are measurable, 0≤un,m≤gm≤m, and gm−un,m is a nonnegative measurable function.

2.1step 1.1L1L2L3L4algebra

Apply [L1] to the sequence gm−un,m. Since gm is finite-valued, lim inf⁡n(gm−un,m)=gm−lim sup⁡nun,m, ∫(gm−un,m) dμ=∫gm dμ−∫un,m dμ, and ∫(gm−lim sup⁡nun,m) dμ=∫gm dμ−∫lim sup⁡nun,m dμ. Rearranging Fatou's inequality therefore gives lim sup⁡n∫un,m dμ≤∫lim sup⁡nun,m dμ≤∫lim sup⁡nfn dμ.

3.1step 2.1L2L3algebra

Since 0≤fn−un,m≤g−gm, [L2] and [L3] give ∫fn dμ=∫un,m dμ+∫(fn−un,m) dμ≤∫un,m dμ+∫(g−gm) dμ. Taking lim sup⁡n and using step 2.1 yields lim sup⁡n∫fn dμ≤∫lim sup⁡nfn dμ+∫(g−gm) dμ.

4.1step 3.1L2L5algebra∎

Because gm↑g, [L5] gives ∫gm dμ↑∫g dμ. Applying [L2] to g=(g−gm)+gm shows ∫(g−gm) dμ=∫g dμ−∫gm dμ⟶0. Letting m→∞ in step 3.1 proves lim sup⁡n∫fn dμ≤∫lim sup⁡nfn dμ.

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

A nonnegative measurable function has integral 0 exactly when it vanishes almost everywhere

Statement

Let f:X→[0,+∞] be measurable. Then ∫f dμ=0⟺f=0 almost everywhere.

Facts & Assumptions

Given: A nonnegative measurable function f.

[L1]

The nonnegative integral is monotone and homogeneous (Monotonicity and nonnegative homogeneity of the nonnegative integral).

[L2]

A statement holds almost everywhere when its exceptional set is contained in a measurable null set (Measure-null sets and almost-everywhere statements relative to a measure).

[L3]

The nonnegative integral is the supremum of the integrals of simple minorants (The nonnegative Lebesgue integral).

[L4]

The nonnegative integral agrees with the defining simple integral on simple functions (The nonnegative integral agrees with the simple integral on simple functions).

Proof

technique · direct
1.1L1L2L4givenalgebra

Assume ∫f dμ=0. For n≥1 let En:={f≥1/n}. Then (1/n)χEn≤f, so [L1] and [L4] give 1nμ(En)=∫(1/n)χEn dμ≤∫f dμ=0. Hence μ(En)=0 for every n. Since {f>0}=⋃nEn, the exceptional set where f≠0 is null, so f=0 almost everywhere by [L2].

1.2L2L3given

Assume f=0 almost everywhere, and let N be a measurable null set containing {f>0}. For any disjoint simple representation s=∑jcjχEj≤f, every Ej with cj>0 lies inside N and has measure zero. Every zero-coefficient term contributes zero, including an omitted complement cell of infinite measure, by the simple integral's 0⋅(+∞)=0 convention. Thus ∫s dμ=0. The now-complete finite refinement proof of The simple integral is independent of the chosen representation makes this value independent of representation. Taking the supremum over all simple minorants in [L3] gives ∫f dμ=0.

2.1step 1.1step 1.2∎

Step 1.1 proves the forward implication and step 1.2 proves the reverse implication.

CorollaryStatement: Literature-sourcedProof: AI-generatedprecheck passverified 2026-09-23 (gpt-6-sol)Open item page →

A nonnegative measurable function with finite integral is finite almost everywhere

Statement

If f:X→[0,+∞] is measurable and ∫f dμ<+∞, then f(x)<+∞ for almost every x.

Facts & Assumptions

Given: A nonnegative measurable function f with finite integral.

[L1]

The nonnegative integral is monotone and homogeneous (Monotonicity and nonnegative homogeneity of the nonnegative integral).

[L2]

The nonnegative integral of the simple function nχF equals its simple integral nμ(F) (The nonnegative integral agrees with the simple integral on simple functions).

Proof

technique · direct
1.1L1L2given

Let F:={f=+∞}, which is measurable. For every positive integer n, nχF≤f. By [L1] and [L2], nμ(F)=∫nχF dμ≤∫f dμ<+∞.

2.1step 1.1algebra∎

If μ(F)>0, the inequalities in step 1.1 fail for sufficiently large n; if μ(F)=+∞, they fail already for n=1. Thus μ(F)=0, so the exceptional set where f is infinite is null. Equivalently, f<+∞ almost everywhere.

CorollaryStatement: Literature-sourcedProof: AI-generatedprecheck passverified 2026-09-23 (gpt-6-sol)Open item page →

A nonnegative integral over a null set vanishes

Statement

Let f:X→[0,+∞] be measurable and let E be measurable with μ(E)=0. Then ∫Ef dμ=0.

Facts & Assumptions

Given: A nonnegative measurable function f and a measurable null set E.

[L1]

The set function A↦∫As dμ is a measure whenever s is nonnegative simple (The indefinite integral of a nonnegative simple function is a measure).

[L2]

The integral over a measurable set is defined by ∫Ef dμ=∫fχE dμ (Integral over a measurable subset).

[L3]

The nonnegative integral is the supremum of the integrals of simple minorants (The nonnegative Lebesgue integral).

Proof

technique · direct
1.1L1L2given

Let s=∑jcjχAj be a nonnegative simple minorant of fχE, with cj≥0. If cj>0, then Aj⊆E because s=0 outside E; hence μ(Aj)=0. The simple-integral formula, equivalently the finite-sum calculation in [L1], gives ∫s dμ=∑jcjμ(Aj)=0, including when the original representation overlaps.

2.1step 1.1L2L3∎

Taking the supremum over all such simple minorants in [L3] gives ∫Ef dμ=∫fχE dμ=0.

CorollaryStatement: Literature-sourcedProof: AI-generatedprecheck passaudited 2026-08-27Open item page →

Almost-everywhere monotone convergence

Statement

Let f be measurable, let 0≤f1≤f2≤⋯ be measurable, and suppose fn↑f almost everywhere. Then ∫fn dμ↑∫f dμ.

Facts & Assumptions

Given: A measurable nonnegative function f and a nondecreasing sequence (fn) of nonnegative measurable functions with fn↑f almost everywhere.

[L1]

Monotone convergence holds when the pointwise increase is everywhere (Monotone convergence for the integral).

[L2]

A nonnegative integral over a measurable null set is 0 (A nonnegative integral over a null set vanishes).

[L3]

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

Proof

technique · direct
1.1L1givenconstruct

Let N be a measurable null set outside which fn↑f, and define gn:=fnχX∖N and g:=fχX∖N.

Then gn↑g everywhere, and g is measurable because f is. So [L1] gives ∫gn dμ↑∫g dμ.

2.1step 1.1L2L3

Each difference fn−gn=fnχN and f−g=fχN is supported on the null set N.

Therefore [L2] and [L3] give

∫fn dμ=∫gn dμ,∫f dμ=∫g dμ.

Substituting into step 1.1 yields the result. [step 1.1, L2, L3] ∎

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

Chebyshev-Markov inequality for the integral

Statement

Let f:X→[0,+∞] be measurable and let t>0. Then μ({f≥t})≤1t∫f dμ.

Facts & Assumptions

Given: A nonnegative measurable function f and a real number t>0.

[L1]

The nonnegative integral is monotone and homogeneous (Monotonicity and nonnegative homogeneity of the nonnegative integral).

[L2]

For measurable E and t>0, the nonnegative integral of the simple function tχE is tμ(E) (The nonnegative integral agrees with the simple integral on simple functions, The integral of a nonnegative simple function).

Proof

technique · direct
1.1L1L2given

Put E:={f≥t}, which is measurable. Since tχE≤f, [L1] and [L2] give t μ(E)=∫tχE dμ≤∫f dμ.

2.1step 1.1algebra∎

Dividing by the positive real t gives μ({f≥t})≤t−1∫f dμ.

DefinitionDefinition: Literature-sourcedProof: Not applicableaudited 2026-08-27Open item page →

Integrable real and complex functions, and their integrals

Definition

Let f:X→R be measurable. Its positive and negative parts are f+:=max⁡{f,0},f−:=max⁡{−f,0}; they are measurable by Closure properties of measurable functions used by the integral and satisfy f=f+−f− and ∣f∣=f++f−.

The Lebesgue integral of a real measurable function is defined whenever at most one of ∫f+ dμ and ∫f− dμ is +∞, in which case ∫f dμ:=∫f+ dμ−∫f− dμ. The function is integrable when both integrals are finite, equivalently when ∫∣f∣ dμ<+∞.

For a complex measurable function h=u+iv with u=Re⁡h, v=Im⁡h (Real and imaginary parts, complex conjugation, and modulus), define h to be integrable when ∣h∣ is integrable, and then define ∫h dμ:=∫u dμ+i∫v dμ.

DefinitionDefinition: Literature-sourcedProof: Not applicablejudge pass (gpt-5.6-terra)audited 2026-08-27Open item page →

The class L1(μ) of integrable functions

Definition

For a measure μ, write L1(μ):={f:X→C: f is integrable}. Here integrable is the notion introduced in Integrable real and complex functions, and their integrals.

On this page L1(μ) is the class of integrable representatives. The later Banach-space page will pass to almost-everywhere equivalence classes.

TheoremStatement: Literature-sourcedProof: AI-generatedprecheck passaudited 2026-08-27Open item page →

The Lebesgue integral is linear on L1(μ)

Statement

The class L1(μ) is a complex vector space, and the Lebesgue integral is complex-linear on it: ∫(αf+βg) dμ=α∫f dμ+β∫g dμ(α,β∈C, f,g∈L1(μ)).

Facts & Assumptions

Given: Integrable functions f,g∈L1(μ) and scalars α,β∈C.

[L1]

Real and complex integrability, together with the decomposition into positive and negative parts and into real and imaginary parts, is defined in Integrable real and complex functions, and their integrals.

[L2]

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

[L3]

The nonnegative integral is monotone and homogeneous (Monotonicity and nonnegative homogeneity of the nonnegative integral).

[L4]

Sums and real scalar multiples of measurable real-valued functions are measurable (Closure properties of measurable functions used by the integral).

Proof

technique · direct
1.1L1L2L3L4algebra

First treat real-valued f,g and put h:=f+g. By [L4], the function h is measurable. Also h+≤f++g+,h−≤f−+g−, so [L2] and [L3] give ∫h+ dμ≤∫f+ dμ+∫g+ dμ<+∞,∫h− dμ≤∫f− dμ+∫g− dμ<+∞. Hence h is integrable. Since h++f−+g−=h−+f++g+, another application of [L2] yields ∫h+ dμ+∫f− dμ+∫g− dμ=∫h− dμ+∫f+ dμ+∫g+ dμ, which rearranges to ∫(f+g) dμ=∫f dμ+∫g dμ.

1.2L1L3L4algebra

Now let c∈R and let f be real-valued. By [L4], cf is measurable. If c≥0, then (cf)+=cf+,(cf)−=cf−; if c<0, then (cf)+=(−c)f−,(cf)−=(−c)f+. In both cases [L3] shows that cf is integrable and that ∫(cf) dμ=c∫f dμ.

2.1L1step 1.1step 1.2algebra∎

Let h=u+iv∈L1(μ) and γ=a+ib∈C. Then γh=(au−bv)+i(av+bu). The real-valued functions au−bv and av+bu are integrable by steps 1.1 and 1.2, and their real-linear integral formulas combine into ∫(γh) dμ=γ∫h dμ. Writing αf=h1+ik1 and βg=h2+ik2 with real-valued integrable hj,kj, step 1.1 gives ∫(αf+βg) dμ=∫(h1+h2) dμ+i∫(k1+k2) dμ=∫h1 dμ+i∫k1 dμ+∫h2 dμ+i∫k2 dμ=α∫f dμ+β∫g dμ.

DefinitionDefinition: AI-adaptedProof: Not applicablejudge pass (gpt-5.6-terra)audited 2026-09-10Open item page →

Measure-preserving transformations and systems

Definition

Let (X,A,μ) be a measure space. A measurable self-map T:X→X is measure preserving if μ(T−1E)=μ(E) for every E∈A. The quadruple (X,A,μ,T) is a measure-preserving system; it is a probability system if μ(X)=1. Here T−1E={x:T(x)∈E} denotes an inverse image, whether or not T is invertible. Neither completeness nor finiteness is implicit. The measure-space and measurable-map conventions are Measure spaces and A measurable function between measurable spaces.

TheoremStatement: AI-adaptedProof: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-10Open item page →

Integral invariance under measure-preserving maps

Statement

If T preserves μ and f:X→[0,∞] is measurable, then ∫f∘T dμ=∫f dμ, allowing infinity. If f is integrable real or complex valued, f∘T is integrable and the same equality holds. Conversely, for a measurable self-map, equality for every measurable indicator implies measure preservation.

Facts & Assumptions

[F1]

Nonnegative measurable functions admit increasing simple approximations Every nonnegative measurable function is the increasing limit of simple measurable functions.

[F2]

Increasing nonnegative measurable functions have increasing integrals with the expected limit Monotone convergence for the integral.

[F3]

The integral is complex-linear on integrable functions The Lebesgue integral is linear on L1(μ).

Proof

Given: The objects and hypotheses in the statement.

1.1given

For E∈A, 1E∘T=1T−1E, hence its integral is μ(T−1E)=μ(E). A nonnegative simple function written over disjoint fibers has integral equal to the sum of coefficient times fiber measure, so the identity holds for every such function, also when the sum is infinite in value.

2.1F1F2step 1.1

For nonnegative measurable f, take sn↑f as supplied by simple approximation. Then sn∘T↑f∘T measurably. Integral monotone convergence on both sides gives ∫f∘T=lim⁡n∫sn∘T=lim⁡n∫sn=∫f.

3.1F3step 2.1

For integrable f, applying step 2.1 to ∣f∣ proves ∫∣f∘T∣=∫∣f∣<∞. Apply that step to the positive and negative parts of each real component. Subtract their finite integrals and combine the real and imaginary parts by linearity to obtain the asserted equality.

4.1step 1.1given∎

Conversely the indicator identity is exactly μ(T−1E)=μ(E) for each measurable E. Thus it is measure preservation.

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

Two integrable functions are equal almost everywhere exactly when all of their indefinite integrals agree

Statement

Let f,g∈L1(μ). Then the following are equivalent:

  1. f=g almost everywhere;
  2. for every measurable A, ∫Af dμ=∫Ag dμ.

For integrable real or complex h, the notation in condition 2 means ∫Ah dμ:=∫hχA dμ; the product is integrable because ∣hχA∣≤∣h∣.

Facts & Assumptions

Given: Integrable functions f,g∈L1(μ).

[L1]

The integral over a null set vanishes for nonnegative integrands (A nonnegative integral over a null set vanishes).

[L2]

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

[L3]

A nonnegative measurable function has integral 0 exactly when it vanishes almost everywhere (A nonnegative measurable function has integral 0 exactly when it vanishes almost everywhere).

[L4]

Real and imaginary parts of an integrable complex function are integrable (Integrable real and complex functions, and their integrals).

Proof

technique · direct
1.1L1L2L4given

Assume f=g almost everywhere, with exceptional null set N. For every measurable A, the positive and negative parts of the real and imaginary components of (f−g)χA are supported on N. By [L1] their nonnegative integrals vanish, and [L2] and [L4] give ∫A(f−g) dμ=0, hence ∫Af dμ=∫Ag dμ.

1.2L2L3L4given

Assume instead that ∫Af dμ=∫Ag dμ for every measurable A. Apply this to the real part u:=Re⁡(f−g) on A+:={u>0} and to −u on A−:={u<0}. In each case the corresponding nonnegative integral is 0, so [L3] gives u=0 almost everywhere. The same argument for v:=Im⁡(f−g) shows v=0 almost everywhere. Hence f=g almost everywhere.

2.1step 1.1step 1.2∎

Step 1.1 proves (1)⇒(2) and step 1.2 proves (2)⇒(1).

TheoremStatement: Literature-sourcedProof: AI-generatedprecheck passaudited 2026-08-27Open item page →

The modulus of an integral is bounded by the integral of the modulus

Statement

If f∈L1(μ), then ∣∫f dμ∣≤∫∣f∣ dμ.

Facts & Assumptions

Given: An integrable function f.

[L1]

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

[L2]

Real and imaginary parts, complex conjugation, and modulus are as in Real and imaginary parts, complex conjugation, and modulus.

[L3]

Real and complex integrability are defined in Integrable real and complex functions, and their integrals.

Proof

technique · direct
1.1L1L3L4algebra

For real-valued f, the functions ∣f∣+f=2f+ and ∣f∣−f=2f− are nonnegative. Therefore [L1] and [L4] give 0≤∫(∣f∣+f) dμ=∫∣f∣ dμ+∫f dμ, 0≤∫(∣f∣−f) dμ=∫∣f∣ dμ−∫f dμ. So −∫∣f∣ dμ≤∫f dμ≤∫∣f∣ dμ, and hence ∣∫f dμ∣≤∫∣f∣ dμ.

2.1L1L2step 1.1L4algebra∎

For complex-valued f, let I:=∫f dμ. If I=0 there is nothing to prove. Otherwise set α:=I‾/∣I∣, so ∣α∣=1 by [L2]. Then ∣I∣=αI=∫αf dμ, and ∣Re⁡(αf)∣≤∣αf∣=∣f∣, so step 1.1 applies to the integrable real-valued function Re⁡(αf). Taking real parts gives ∣I∣=∫Re⁡(αf) dμ≤∫∣αf∣ dμ=∫∣f∣ dμ, because Re⁡z≤∣z∣ for every complex z.

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

Dominated convergence

Statement

Let f and (fn) be measurable complex-valued functions such that fn→f almost everywhere and ∣fn∣≤g almost everywhere for a single nonnegative measurable function g with ∫g dμ<+∞. Then f∈L1(μ), ∫∣fn−f∣ dμ⟶0, and hence ∫fn dμ⟶∫f dμ.

Facts & Assumptions

Given: Measurable complex-valued functions f,fn with fn→f almost everywhere and ∣fn∣≤g almost everywhere for one nonnegative measurable function g of finite integral.

[L1]

Reverse Fatou's lemma holds under an integrable majorant (Reverse Fatou's lemma under an integrable majorant).

[L2]

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

[L3]

The integral triangle inequality holds on L1(μ) (The modulus of an integral is bounded by the integral of the modulus).

[L4]

Real and complex integrability are defined in Integrable real and complex functions, and their integrals.

[L5]

The nonnegative integral is additive, and a nonnegative integral over a null set vanishes (Additivity of the nonnegative Lebesgue integral, A nonnegative integral over a null set vanishes).

[L6]

A nonnegative measurable function with finite integral is finite almost everywhere (A nonnegative measurable function with finite integral is finite almost everywhere).

[L7]

The nonnegative integral is monotone and homogeneous (Monotonicity and nonnegative homogeneity of the nonnegative integral).

Proof

technique · direct
1.1L4L5L6L7given

Let N0 be a measurable null set outside which fn(x)→f(x) and ∣fn(x)∣≤g(x) for every n, and let N∞:={g=∞}. By [L6], the set N∞ is null. Put N:=N0∪N∞, E:=X∖N, g~:=gχE,hn:=∣fn−f∣χE. Then hn→0 pointwise, 0≤hn≤2g~, and g~ is nonnegative, measurable, and finite everywhere. Also ∣f∣≤∣f∣χN+g~. By [L5] and [L7], ∫∣f∣ dμ≤∫∣f∣χN dμ+∫g~ dμ=0+∫g~ dμ≤∫g dμ<+∞, so f∈L1(μ) by [L4]. The same null-set and domination argument gives ∫∣fn∣ dμ≤∫g dμ<∞ for each n, so every fn also belongs to L1(μ).

2.1step 1.1L1

The functions hn are nonnegative, converge pointwise to 0, and are dominated by the finite everywhere majorant 2g~. Applying [L1] therefore gives lim sup⁡n∫hn dμ≤∫0 dμ=0. Hence ∫hn dμ→0.

3.1step 1.1step 2.1L2L3L5∎

Because ∣fn−f∣χN is supported on the null set N, [L5] gives ∫∣fn−f∣ dμ=∫hn dμ+∫∣fn−f∣χN dμ=∫hn dμ⟶0. Therefore, by [L2] and [L3], ∣∫fn dμ−∫f dμ∣=∣∫(fn−f) dμ∣≤∫∣fn−f∣ dμ, and the right-hand side tends to 0.

CorollaryStatement: Literature-sourcedProof: AI-generatedprecheck passaudited 2026-08-27Open item page →

Bounded convergence on a finite measure space

Statement

Let (X,A,μ) be a finite measure space and let f and (fn) be measurable complex-valued functions with fn→f almost everywhere. If ∣fn∣≤M almost everywhere for one real M≥0, then ∫fn dμ⟶∫f dμ.

Facts & Assumptions

Given: A finite measure space, measurable complex-valued functions f,fn with fn→f almost everywhere, and a uniform bound ∣fn∣≤M.

[L1]

Dominated convergence applies whenever one integrable dominating function controls the whole sequence (Dominated convergence).

Proof

technique · direct
1.1givenalgebra

The constant function g:=MχX is integrable because ∫g dμ=Mμ(X)<+∞. It dominates every fn.

2.1step 1.1L1∎

Apply [L1] with the dominating function from step 1.1.

TheoremStatement: Literature-sourcedProof: AI-generatedprecheck passaudited 2026-08-27Open item page →

Integrable simple functions are dense in L1(μ)

Statement

For every f∈L1(μ) there is a sequence of integrable simple functions (sn) such that ∫∣f−sn∣ dμ⟶0.

Facts & Assumptions

Given: An integrable function f.

[L1]

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

[L2]

Real and complex integrability are defined in Integrable real and complex functions, and their integrals.

[L3]

Dominated convergence gives L1 convergence under an integrable majorant (Dominated convergence).

Proof

technique · direct
1.1L1L2L3construct

Suppose first that f is real-valued. Choose simple un↑f+ and vn↑f− by [L1], and put sn:=un−vn. Then sn is an integrable simple function and ∣f−sn∣=(f+−un)+(f−−vn)↓0, with ∣f−sn∣≤∣f∣. By [L3], ∫∣f−sn∣ dμ→0.

2.1step 1.1L2L4∎

For complex f=u+iv, apply step 1.1 separately to u and v to obtain real simple functions pn,qn with ∫∣u−pn∣ dμ→0,∫∣v−qn∣ dμ→0. Set sn:=pn+iqn. Then sn is a simple integrable function and ∣f−sn∣≤∣u−pn∣+∣v−qn∣. By [L4], ∫∣f−sn∣ dμ≤∫∣u−pn∣ dμ+∫∣v−qn∣ dμ⟶0, so (sn) converges to f in L1.

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

Absolute continuity of the integral

Statement

Let f∈L1(μ) and let ε>0. Then there is δ>0 such that for every measurable E, μ(E)<δ⟹∫E∣f∣ dμ<ε.

Facts & Assumptions

Given: An integrable function f and a real number ε>0.

[L1]

The truncations ∣f∣∧n increase pointwise to ∣f∣, so their integrals converge to ∫∣f∣ dμ by monotone convergence (Monotone convergence for the integral).

[L2]

The integral over a measurable set is defined by ∫Eh dμ=∫hχE dμ (Integral over a measurable subset).

[L3]

The nonnegative integral is monotone and homogeneous (Monotonicity and nonnegative homogeneity of the nonnegative integral).

[L4]

Integrability means ∫∣f∣ dμ<+∞ (Integrable real and complex functions, and their integrals).

[L5]

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

Proof

technique · direct
1.1L1L4L5choose

Put hn=∣f∣−∣f∣∧n≥0. The pointwise identity ∣f∣=(∣f∣∧n)+hn and [L5] give ∫hn=∫∣f∣−∫(∣f∣∧n); the subtraction is valid because both integrals are finite by [L4]. By [L1] choose n so large that ∫hn dμ<ε/2, and put δ:=ε/(2n+1).

2.1step 1.1L2L3L5algebra∎

If μ(E)<δ, then [L2], [L3], and [L5] give ∫E∣f∣ dμ=∫E(∣f∣∧n) dμ+∫Ehn dμ≤nμ(E)+∫hn dμ<nδ+ε/2<ε. The last inequality follows from n/(2n+1)<1/2.

PropositionStatement: Literature-sourcedProof: AI-generatedprecheck passaudited 2026-08-27Open item page →

The indefinite integral of an integrable function is countably additive on measurable sets

Statement

If f∈L1(μ) and νf(A):=∫fχA dμ(A∈A), then νf is countably additive on pairwise disjoint measurable families. Here fχA is integrable because ∣fχA∣≤∣f∣; this formula defines the notation ∫Af dμ for integrable real or complex f.

Facts & Assumptions

Given: An integrable function f.

[L1]

For every nonnegative measurable h, the set function A↦∫Ah dμ is a measure (The indefinite integral of a nonnegative measurable function is a measure).

[L2]

Real and complex integrability are defined by positive/negative parts and by real/imaginary parts (Integrable real and complex functions, and their integrals).

[L3]

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

Proof

technique · direct
1.1

For real-valued f, write f=f+−f−. Then [L1, L2, L3] νf=νf+−νf−, and both νf+ and νf− are measures by [L1]. Because f∈L1(μ), the total masses of those measures are finite, so subtracting their countably additive values on a disjoint family is legitimate and gives countable additivity of νf.

2.1

For complex-valued f=u+iv, one has [step 1.1, L2, L3] ∎ νf=νu+iνv, and step 1.1 applies to the real-valued functions u and v. Therefore νf is countably additive as well.

TheoremStatement: Literature-sourcedProof: AI-generatedprecheck passaudited 2026-08-27Open item page →

Continuity under the integral sign

Statement

Let I⊆R be an interval and let f:X×I→C be such that:

  1. for every t∈I, the function x↦f(x,t) is integrable;
  2. for almost every x, the map t↦f(x,t) is continuous on I;
  3. there is a nonnegative measurable function g with ∫g dμ<+∞ and ∣f(x,t)∣≤g(x) for every t∈I and almost every x.

Then F(t):=∫f(x,t) dμ(x) is continuous on I.

Facts & Assumptions

Given: An interval I and a function f satisfying the three displayed hypotheses.

[L1]

Dominated convergence applies to integrable complex-valued functions under a single L1 majorant (Dominated convergence).

Proof

technique · direct
1.1givenL1

Fix t0∈I and let (tn) be any sequence in I with tn→t0. For almost every x, continuity in t gives f(x,tn)→f(x,t0), and the dominating bound gives ∣f(x,tn)∣≤g(x).

2.1step 1.1L1∎

Apply [L1] to the sequence x↦f(x,tn). Then F(tn)=∫f(x,tn) dμ(x)⟶∫f(x,t0) dμ(x)=F(t0). Since every convergent sequence in I has this property, F is continuous at t0, and therefore on all of I.

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

Differentiation under the integral sign

Statement

Let I⊆R be an open interval and let f:X×I→C be such that:

  1. for every t∈I, the function x↦f(x,t) is integrable;
  2. for almost every x, the map t↦f(x,t) is differentiable on I;
  3. for every t∈I, the function x↦∂f∂t(x,t), extended by zero where the derivative is undefined, is measurable;
  4. there are a measurable null set N and a nonnegative measurable function g with ∫g dμ<+∞ and ∣∂f∂t(x,t)∣≤g(x) for every t∈I and every x∈X∖N.

Then F(t):=∫f(x,t) dμ(x) is differentiable on I, and F′(t)=∫∂f∂t(x,t) dμ(x), with the same zero extension in the last integral.

Facts & Assumptions

Given: An open interval I, a function f satisfying the first three displayed hypotheses, and a measurable null set N together with a nonnegative measurable majorant g satisfying hypothesis 4. Choose a measurable null set E outside which hypothesis 2 holds, and put N∗=N∪E.

[L1]

Dominated convergence applies to integrable complex-valued functions under a single L1 majorant (Dominated convergence).

[L3]

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

[L4]

The rationals are dense in the reals (The rationals embed densely in the reals).

Proof

technique · direct
1.1givenconstruct

Fix t0∈I and let hn→0 with hn≠0 and t0+hn∈I. Define qn(x):=f(x,t0+hn)−f(x,t0)hn. For every x∈X∖N∗, differentiability in t gives qn(x)→∂tf(x,t0). Give the derivative value zero on N∗; this measurable modification differs from the stated zero extension only on a null set, so it has the same integral.

2.1step 1.1L1L2

For each n, hypothesis 1 makes x↦f(x,t0+hn) and x↦f(x,t0) integrable and therefore measurable, so qn is measurable. Fix x∈X∖N∗ and n. If qn(x)=0, then ∣qn(x)∣≤g(x) is immediate. Otherwise put α:=qn(x)‾/∣qn(x)∣, so ∣α∣=1 and ∣qn(x)∣=Re⁡ ⁣(α f(x,t0+hn)−f(x,t0)hn). Apply [L2] to the real-valued function τ↦Re⁡(αf(x,τ)) on the segment joining t0 to t0+hn. For some interior point ξ of that segment, ∣qn(x)∣=Re⁡(α ∂tf(x,ξ))≤∣∂tf(x,ξ)∣≤g(x). Hypothesis 3 and the zero extension make the limit measurable. Therefore [L1] applies to (qn).

3.1step 2.1L1L3

By [L1], lim⁡n∫qn(x) dμ(x)=L:=∫∂tf(x,t0) dμ(x). Linearity of the integral gives ∫qn(x) dμ(x)=F(t0+hn)−F(t0)hn. This holds for every supplied sequence of admissible nonzero increments.

4.1L2L4step 2.1step 3.1∎

The same mean-value estimate as in step 2.1, with any s,t∈I in place of t0,t0+hn, gives ∣f(x,t)−f(x,s)∣≤∣t−s∣g(x) outside N∗. Integrating yields ∣F(t)−F(s)∣≤∣t−s∣∫g dμ, so F is continuous. Consequently Q(h)=(F(t0+h)−F(t0))/h is continuous on the punctured interval of admissible increments. If Q(h) failed to tend to L as h→0, there would be an ε>0 and, for every n≥1, a nonzero admissible h with ∣h∣<1/n and ∣Q(h)−L∣≥ε. Continuity of Q and [L4] give a rational admissible r with ∣r∣<1/n and ∣Q(r)−L∣>ε/2. Fix an enumeration of Q and take the first such rational rn for each n; this is a definable selection from a countable set and uses no Countable Choice. Then rn→0, contradicting step 3.1. Thus Q(h)→L, which is precisely F′(t0)=L. Since t0 was arbitrary, the theorem follows.

TheoremStatement: Literature-sourcedProof: AI-generatedprecheck passaudited 2026-08-27Open item page →

Jensen's integral inequality for a probability measure

Statement

Let (X,A,P) be a probability space, let f∈L1(P) be real-valued, let I⊆R be an interval containing f(x) for almost every x, and let φ:I→R be convex with φ∘f∈L1(P). Then φ ⁣(∫f dP)≤∫φ(f) dP.

Facts & Assumptions

Given: A probability space (X,A,P), a real-valued integrable f, an interval I containing its almost-everywhere range, and a convex φ:I→R with φ∘f∈L1(P).

[L1]

A probability measure is a measure with total mass 1 (Probability measures and probability spaces).

[L2]

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

[L3]

Every slope between the one-sided derivatives of a convex function yields a supporting line at an interior point (Every slope between the left and right derivatives of a convex function gives a supporting line).

[L4]

A nonnegative measurable function has integral 0 exactly when it vanishes almost everywhere (A nonnegative measurable function has integral 0 exactly when it vanishes almost everywhere).

Proof

technique · direct
1.1L1L2L3givenalgebra

Put m:=∫f dP. If m lies in the interior of I, apply [L3] to obtain a supporting line ℓ(x)=φ(m)+a(x−m) with ℓ(x)≤φ(x) on I. Integrating and using [L1] and [L2] gives ∫φ(f) dP≥∫ℓ(f) dP=φ(m)+a(∫f dP−m∫1 dP)=φ(m).

1.2

Suppose instead that m is an endpoint of I, say the left endpoint. Then [L1, L2, L4, given] f−m≥0 almost everywhere and ∫(f−m) dP=∫f dP−m∫1 dP=0 by [L1] and [L2]. Therefore f=m almost everywhere by [L4], so ∫φ(f) dP=φ(m)=φ ⁣(∫f dP). The right-endpoint case is identical.

2.1

Steps 1.1 and 1.2 cover the interior and endpoint cases, so Jensen's [step 1.1, step 1.2] ∎ inequality holds on the whole interval I.

False statementConstruction: AI-adaptedVerification: AI-generatedprecheck passaudited 2026-08-27Open item page →

FALSE: monotone convergence holds without monotonicity

Statement

If fn:X→[0,+∞] are measurable and converge pointwise to f, then ∫fn dμ→∫f dμ.

Facts & Assumptions

Given: The statement above.

[L1]

Monotone convergence requires a nondecreasing hypothesis (Monotone convergence for the integral).

Refutation

technique · direct
1.1

On (0,1) with Lebesgue measure, let [given, construct] fn:=(n+1)χ(0,1/(n+1)); then fn(x)→0 for every x∈(0,1).

2.1step 1.1L1algebra∎

But ∫fn dμ=1 for every n, whereas ∫0 dμ=0. So the displayed conclusion fails, and [L1] shows that the missing monotonicity hypothesis is exactly what breaks.

False statementConstruction: AI-adaptedVerification: AI-generatedprecheck passaudited 2026-08-27Open item page →

FALSE: Fatou's lemma is always an equality

Statement

For every sequence of nonnegative measurable functions (fn), ∫lim inf⁡nfn dμ=lim inf⁡n∫fn dμ.

Facts & Assumptions

Given: The statement above.

[L1]

Fatou's lemma only asserts the inequality ≤ (Fatou's lemma).

Refutation

technique · direct
1.1givenconstruct

On R with Lebesgue measure, let fn:=χ[n,n+1]; then lim inf⁡nfn=0 pointwise.

2.1step 1.1L1algebra∎

Therefore ∫lim inf⁡nfn dμ=0, while ∫fn dμ=1 for every n. So the equality in the Statement fails, and [L1] is strict here.

False statementConstruction: AI-adaptedVerification: AI-generatedprecheck passaudited 2026-08-27Open item page →

FALSE: dominated convergence holds without a dominating function

Statement

If fn→f almost everywhere and each fn is integrable, then ∫fn dμ→∫f dμ.

Facts & Assumptions

Given: The statement above.

[L1]

Dominated convergence spends one integrable majorant for the whole sequence (Dominated convergence).

Refutation

technique · direct
1.1

On (0,1) with Lebesgue measure, let [given, construct] fn:=(n+1)χ(0,1/(n+1)). Then fn→0 almost everywhere and every fn is integrable.

2.1step 1.1L1algebra∎

However ∫fn dμ=1 for every n, while ∫0 dμ=0. So the conclusion fails, and [L1] identifies the missing dominating function as the lost hypothesis.

False statementConstruction: AI-adaptedVerification: AI-generatedprecheck passaudited 2026-08-27Open item page →

FALSE: a nonnegative measurable function with integral 0 vanishes everywhere

Statement

If f:X→[0,+∞] is measurable and ∫f dμ=0, then f(x)=0 for every x.

Facts & Assumptions

Given: The statement above.

[L1]

A nonnegative measurable function has integral 0 exactly when it vanishes almost everywhere, not everywhere (A nonnegative measurable function has integral 0 exactly when it vanishes almost everywhere).

Refutation

technique · direct
1.1

On R with Lebesgue measure, let f:=χ{0}. By [L2], the [L2, given, construct] set {0} is null, so ∫f dλ=0.

1.2step 1.1L1∎

But f(0)=1. Therefore the conclusion in the Statement is false, and [L1] shows that "almost everywhere" is the correct replacement.

False statementConstruction: AI-adaptedVerification: AI-generatedprecheck passaudited 2026-08-27Open item page →

FALSE: pointwise limits of integrable functions are integrable

Statement

Whenever integrable functions fn converge pointwise to f, the limit f is integrable.

Facts & Assumptions

Given: The statement above.

[L1]
[L2]

Integrability means finiteness of the integral of the modulus (Integrable real and complex functions, and their integrals).

Refutation

technique · direct
1.1

On (N,P(N),#), let [L1, L2, given, construct] fn:=χ{0,…,n}. Each fn is integrable because it has finite support, and fn(k)→1 for every k∈N.

2.1

The pointwise limit is the constant function 1, whose counting-measure [step 1.1, L1, L2, algebra] ∎ integral is +∞, so it is not integrable by [L2]. Therefore the Statement is false.

False statementConstruction: AI-adaptedVerification: AI-generatedprecheck passaudited 2026-08-27Open item page →

FALSE: the Lebesgue integral extends linearly to all measurable functions

Statement

Whenever measurable real-valued functions f, g, and f+g all have defined extended Lebesgue integrals, the extended-real sum ∫f dμ+∫g dμ is defined and equals ∫(f+g) dμ.

Facts & Assumptions

Given: The statement above.

[L1]

The actual linearity theorem only applies on L1(μ) (The Lebesgue integral is linear on L1(μ)).

Refutation

technique · direct
1.1givenconstruct

On R with Lebesgue measure, let f:=χ[0,∞); its nonnegative Lebesgue integral is +∞.

2.1step 1.1L1algebra∎

The integrals of f, −f, and f−f=0 are individually defined, with [step 1.1, L1, algebra] values +∞, −∞, and 0. But ∫f dλ+∫(−f) dλ=+∞+(−∞) is undefined, so the claimed unrestricted linearity identity fails. This is why [L1] restricts linearity to L1.

False statementConstruction: AI-adaptedVerification: AI-generatedprecheck passaudited 2026-08-27Open item page →

FALSE: Jensen's inequality holds on an infinite measure space without normalization

Statement

For every convex φ and every nonnegative measurable f one has φ ⁣(∫f dμ)≤∫φ(f) dμ, even when μ(X)≠1.

Facts & Assumptions

Given: The statement above.

[L1]

Jensen's inequality is stated for probability measures, so the normalization μ(X)=1 is part of the theorem (Jensen's integral inequality for a probability measure).

[L2]

Refutation

technique · direct
1.1

On (N,P(N),#), let f:=χ{1,2} and[L2, given, construct] φ(x):=x2. Then ∫f d#=2,∫φ(f) d#=2.

2.1

Therefore [step 1.1, L1, algebra] ∎ φ ⁣(∫f d#)=4>2=∫φ(f) d#, so the displayed inequality fails on this infinite measure space. This is why [L1] requires probability normalization.

5 · Examples, counterexamples and false statements

None yet.

Sources