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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:XR is measurable when f1(B)A for every BB(R).

Equivalently, it is enough to require {xX:f(x)>a}Afor every aR, 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,,EmA and coefficients c1,,cm[0,+) such that s=j=1mcjχEj. Any such display is a simple representation of s.

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

Closure properties of measurable functions used by the integral

Statement

Let (X,A,μ) be a measure space.

  1. If f,g:XR are measurable and f+g is defined pointwise, then f+g is measurable.
  2. If cR and f:XR is measurable, then cf is measurable.
  3. If f:XR is measurable, then f+=max{f,0}, f=max{f,0}, and f=f++f are measurable.
  4. If EA and f:X[0,+] is measurable, then fχE is measurable.
  5. If (fn) is a sequence of measurable functions XR, then infnfn is measurable; if moreover fnf 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:XR is measurable exactly when {h>a}A for every real a (Extended-real-valued measurable functions).

Proof

technique · direct
1.1

If f+g is defined pointwise, then for every real a, [L1, algebra] {f+g>a}=qQ({f>q}{g>aq}), so clause 1 follows from [L1].

1.2

For c0 one has {cf>a}={f>a/c} when c>0 and [L1, algebra] {cf>a}={f<a/c} when c<0; for c=0 the function is constant. Applying [L1] proves clause 2. The formulas f+=max{f,0} and f=max{f,0} therefore give clause 3.

2.1

If EA and f0, then [L1, algebra] ∎ {fχE>a}=E{f>a}(a>0), so clause 4 follows from [L1]. Also {infnfn>a}=n{fn>a},{supnfn>a}=n{fn>a}, so clause 5 follows from [L1] as well, including the monotone-limit case f=supnfn.

TheoremStatement: Literature-sourcedProof: AI-generatedprecheck passjudge pass (gpt-5.6-terra)audited 2026-08-27Open 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 xX.

Facts & Assumptions

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

[L1]

For a measurable f, the sets f1(B) are measurable for every Borel BR (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
1.1

Set s0:=0. For n1 and 0k<n2n, put [L1, L2, construct] En,k:={x:k2nf(x)<(k+1)2n}{f<n}, and set sn:=k=0n2n1k2nχEn,k+nχ{fn}. Each En,k and {fn} is measurable by [L1], the range of sn is finite, and therefore each sn is simple by [L2]; s0 is also simple.

2.1

For each x, one has 0sn(x)f(x). If f(x)<+ and [step 1.1, algebra] n>f(x), then f(x)2n<sn(x)f(x); if f(x)=+, then sn(x)=n. Hence sn(x)f(x).

3.1

The functions are increasing. Indeed, sn(x) is a dyadic multiple of [step 2.1, L3, algebra] ∎ 2n below f(x)n, hence also a dyadic multiple of 2(n+1) below f(x)(n+1); so the defining maximality of the (n+1)-st dyadic truncation gives sn(x)sn+1(x). Therefore snf, in accord with [L3].

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 EjA are pairwise disjoint and cj0. Its simple integral is sdμ:=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 sdμ 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 sdμ=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
1.1

For each pair (i,j) put Gij:=EiFj. The family (Gij) is [given, L2] measurable and pairwise disjoint, and Ei=jGij,Fj=iGij. Whenever Gij, the two simple formulas for s agree on Gij, so ci=dj.

2.1

Finite additivity over the partitions in step 1.1 gives[step 1.1, L1, L2, algebra] iciμ(Ei)=i,jciμ(Gij)=i,jdjμ(Gij)=jdjμ(Fj). If some coefficient is 0 on a cell of infinite measure, the convention in [L1] forces both corresponding terms to be 0, so no ambiguity occurs there either.

3.1

Therefore the simple integral does not depend on the chosen representation, [step 2.1, L1] ∎ and the definition in [L1] is well defined.

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 c0.

  1. If st pointwise, then sdμtdμ.
  2. csdμ=csdμ.
  3. (s+t)dμ=sdμ+tdμ.

Facts & Assumptions

Given: Nonnegative simple measurable functions s,t and a scalar c0.

[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
1.1

Choose one finite measurable partition (Er) on which both s and t [L1, construct] are constant, say s=rarχEr and t=rbrχEr. Then arbr for every r because st.

2.1

Using the common partition from step 1.1 and [L2], [step 1.1, L2, algebra] sdμ=rarμ(Er),tdμ=rbrμ(Er),csdμ=rcarμ(Er), and (s+t)dμ=r(ar+br)μ(Er). Termwise comparison gives monotonicity, while ordinary finite-sum algebra gives homogeneity and additivity.

3.1

Therefore all three properties hold for the simple integral.

step 2.1
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 fdμ:=sup{sdμ: s is nonnegative simple and 0sf}, 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 passjudge pass (gpt-5.6-terra)audited 2026-08-27Open 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: sdμ=simplesdμ.

Facts & Assumptions

Given: A nonnegative simple measurable function s.

[L1]

The nonnegative integral is the supremum of the simple integrals of all simple minorants 0us (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
1.1

The function s is one of its own admissible simple minorants, so [L1] gives sdμsimplesdμ.

givenL1L3
1.2

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

L1L2L3
2.1

The two inequalities from steps 1.1 and 1.2 are equalities, so the two [step 1.1, step 1.2] ∎ integrals agree on simple functions.

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 EA. Since Closure properties of measurable functions used by the integral implies that fχE is measurable, define the integral of f over E by Efdμ:=fχEdμ, where the integral on the right is the nonnegative Lebesgue integral of The nonnegative Lebesgue integral.

TheoremStatement: Literature-sourcedProof: AI-generatedprecheck passaudited 2026-08-27Open 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):=Asdμ(AA). 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 AAsdμ is defined as AsχAdμ (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).

[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
1.1

Write s=j=1mcjχEj. Then for every measurable A,[L1, L2, given, algebra] νs(A)=Asdμ=j=1mcjμ(AEj).

2.1

Step 1.1 gives νs()=0. If (An) is a pairwise disjoint[step 1.1, L2, L3, algebra] measurable sequence, then each (AnEj) is pairwise disjoint, so νs ⁣(nAn)=j=1mcjμ ⁣(n(AnEj))=j=1mcjnμ(AnEj)=nνs(An).

3.1

Therefore νs satisfies the two conditions in [L3], so it is a [step 2.1, L3] ∎ 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 c0.

  1. If fg, then fdμgdμ.
  2. cfdμ=cfdμ.

Facts & Assumptions

Given: Nonnegative measurable functions f,g and a scalar c0.

[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).

Proof

technique · direct
1.1

If fg, every simple minorant of f is also a simple minorant of g. [L1, given] Taking suprema in [L1] gives fdμgdμ.

1.2

If c=0, both sides are 0. Assume c>0. Multiplication by c carries [L1, L2, given, algebra] simple minorants of f bijectively onto simple minorants of cf, and [L2] scales their integrals by the same factor. Taking suprema in [L1] yields cfdμ=cfdμ.

2.1

Steps 1.1 and 1.2 prove the monotonicity and nonnegative homogeneity rules.

step 1.1step 1.2
TheoremStatement: Literature-sourcedProof: AI-generatedprecheck passaudited 2026-08-27Open item page →

Monotone convergence for the integral

Statement

Let 0f1f2 be measurable and suppose fn(x)f(x) for every x. Then fndμfdμ.

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 AAsdμ 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
1.1

By [L1], the numbers fndμ increase and satisfy[given, L1] fndμfdμ for every n. So their supremum L exists in [0,+] and Lfdμ.

1.2

Fix a nonnegative simple function sf and a real c with 0<c<1.[given, L2, L3] Put An:={fncs}. Then AnX: if s(x)=0 then xAn for all n, while if s(x)>0 then fn(x)f(x)s(x)>cs(x), so eventually xAn. Since AAsdμ is a measure by [L2], [L3] gives AnsdμXsdμ.

2.1

On An one has csfn, hence csχAnfn. By [L1] and [L4],[step 1.2, L1, L4, algebra] cAnsdμ=csχAndμfndμL. Letting n in step 1.2 yields csdμL. Now choose cm=12m and let m; then sdμL.

3.1

Step 2.1 holds for every simple minorant sf, so taking the supremum [step 1.1, step 2.1, given] ∎ over such s gives fdμL by the definition of the nonnegative integral. Together with step 1.1, this proves L=fdμ, so fndμfdμ.

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

Additivity of the nonnegative Lebesgue integral

Statement

If f,g:X[0,+] are measurable, then (f+g)dμ=fdμ+gdμ.

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
1.1

Choose simple functions snf and tng by [L1]. Then [L1, L2, construct] sn+tn is simple for each n, and sn+tnf+g by [L2].

2.1

By [L3] and [L4],[step 1.1, L3, L4, algebra] ∎ (f+g)dμ=limn(sn+tn)dμ=limn(sndμ+tndμ)=fdμ+gdμ.

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=0fk. Then Sdμ=k=0fkdμ.

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 SnS pointwise.

2.1

By [L2], Sndμ=k<nfkdμ for every n. Applying [step 1.1, L2, L3, algebra] ∎ [L3] to step 1.1 gives Sdμ=limnSndμ=limnk<nfkdμ, which is exactly the displayed series identity.

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

The indefinite integral of a nonnegative measurable function is a measure

Statement

Let f:X[0,+] be measurable and define νf(A):=Afdμ(AA). Then νf is a measure on (X,A).

Facts & Assumptions

Given: A nonnegative measurable function f.

[L1]

The set function AAfdμ is defined by AfχAdμ (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
1.1

One has νf()=0. If (An) is a pairwise disjoint sequence,[L1, L2, given] put Bn:=k<nAk. Then χBnχkAk, so fχBnfχkAk and [L2] gives νf ⁣(kAk)=limnνf(Bn).

2.1

Because the sets Ak are disjoint, repeated use of [L3] gives [step 1.1, L3, algebra] νf(Bn)=k<nνf(Ak). Substituting this into step 1.1 proves countable additivity.

3.1

Steps 1.1 and 2.1 verify the two conditions in [L4], so νf is a [step 1.1, step 2.1, L4] ∎ 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 fdμ:A[0,+],(fdμ)(A):=Afdμ, whose measure property is supplied by The indefinite integral of a nonnegative measurable function is a measure.

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

Integrating against a density agrees with integrating the product

Statement

Let f,g:X[0,+] be measurable. Then gd(fdμ)=gfdμ.

Facts & Assumptions

Given: Nonnegative measurable functions f and g.

[L1]

The density measure is defined by (fdμ)(A)=Afdμ (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
1.1

Suppose first that g=j=1mcjχEj is a simple representation, so the sets Ej are pairwise disjoint. Applying [L5] on the measure space (X,A,fdμ) and then using [L1], one gets.

L1L2L5givenalgebra

gd(fdμ)=j=1mcj(fdμ)(Ej)=j=1mcjEjfdμ.

Also gf=j=1mcjfχEj, and the summands have pairwise disjoint supports. Therefore [L2] and [L5] give

gfdμ=j=1mcjfχEjdμ=j=1mcjEjfdμ.

Hence gd(fdμ)=gfdμ.

2.1

For general measurable g0, choose simple gng by [L3]. Then gnfgf pointwise. Applying [L4] twice and step 1.1 to each gn yields.

step 1.1L3L4

gd(fdμ)=limngnd(fdμ)=limngnfdμ=gfdμ.

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

Fatou's lemma

Statement

Let (fn) be nonnegative measurable functions. Then lim infnfndμlim infnfndμ.

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
1.1

For each n, define [L1, given, construct] gn:=infknfk. Then each gn is measurable by [L1], one has gngn+1 and gnlim infnfn pointwise. Also gnfn for every n.

2.1

By [L2], [step 1.1, L2, L3] ∎ lim infnfndμ=limngndμ. Since gnfn, [L3] gives gndμfndμ for every n. Taking the limit in n yields the claimed inequality.

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 gdμ<+ and fng for every n. Then lim supnfndμlim supnfndμ.

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
1.1

For each m1, put gm:=gm and un,m:=fnm. Then gm and un,m are measurable, 0un,mgmm, and gmun,m is a nonnegative measurable function.

L4givenconstruct
2.1

Apply [L1] to the sequence gmun,m. Since gm is finite-valued, lim infn(gmun,m)=gmlim supnun,m, (gmun,m)dμ=gmdμun,mdμ, and (gmlim supnun,m)dμ=gmdμlim supnun,mdμ. Rearranging Fatou's inequality therefore gives lim supnun,mdμlim supnun,mdμlim supnfndμ.

step 1.1L1L2L3L4algebra
3.1

Since 0fnun,mggm, [L2] and [L3] give fndμ=un,mdμ+(fnun,m)dμun,mdμ+(ggm)dμ. Taking lim supn and using step 2.1 yields lim supnfndμlim supnfndμ+(ggm)dμ.

step 2.1L2L3algebra
4.1

Because gmg, [L5] gives gmdμgdμ. Applying [L2] to g=(ggm)+gm shows (ggm)dμ=gdμgmdμ0. Letting m in step 3.1 proves lim supnfndμlim supnfndμ.

step 3.1L2L5algebra
TheoremStatement: Literature-sourcedProof: AI-generatedprecheck passaudited 2026-08-27Open item page →

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

Statement

Let f:X[0,+] be measurable. Then fdμ=0f=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).

Proof

technique · direct
1.1

Assume fdμ=0. For n1 let En:={f1/n}. Then[L1, L2, given, algebra] (1/n)χEnf, so [L1] gives 1nμ(En)=(1/n)χEndμfdμ=0. Hence μ(En)=0 for every n. Since {f>0}=nEn, the exceptional set where f0 is null, so f=0 almost everywhere by [L2].

1.2

Assume f=0 almost everywhere, and let N be a measurable null set[L2, L3, given] containing {f>0}. If s=jcjχEj is a simple minorant of f, then every set Ej with cj>0 lies inside {f>0}N, so μ(Ej)=0; the remaining coefficients are 0. Therefore sdμ=0. Taking the supremum over all simple minorants in [L3] gives fdμ=0.

2.1

Step 1.1 proves the forward implication and step 1.2 proves the reverse [step 1.1, step 1.2] ∎ implication.

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

A nonnegative measurable function with finite integral is finite almost everywhere

Statement

If f:X[0,+] is measurable and fdμ<+, 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]

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
1.1

Let F:={f=+}. Then F{fn} for every n1, so[L1, given] nχFf. By [L1], nμ(F)=nχFdμfdμ<+.

2.1

If μ(F)>0, the inequality in step 1.1 would fail for large n. [step 1.1, L2] ∎ Therefore μ(F)=0, so the indicator χF has integral 0 and hence vanishes almost everywhere by [L2]. Equivalently, f<+ almost everywhere.

CorollaryStatement: Literature-sourcedProof: AI-generatedprecheck passaudited 2026-08-27Open 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 Efdμ=0.

Facts & Assumptions

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

[L1]

The set function AAsdμ 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 Efdμ=fχEdμ (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
1.1

Let s=jcjχAj be a simple minorant of fχE. If cj>0,[L1, L2, given] then AjE, so μ(Aj)=0. Since AAsdμ is a measure by [L1], every positive-coefficient term contributes 0, and the zero-coefficient terms contribute 0 as well. Hence sdμ=0.

2.1

Taking the supremum over all such simple minorants in [L3] gives[step 1.1, L2, L3] ∎ Efdμ=fχEdμ=0.

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

Almost-everywhere monotone convergence

Statement

Let f be measurable, let 0f1f2 be measurable, and suppose fnf almost everywhere. Then fndμfdμ.

Facts & Assumptions

Given: A measurable nonnegative function f and a nondecreasing sequence (fn) of nonnegative measurable functions with fnf 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
1.1

Let N be a measurable null set outside which fnf, and define gn:=fnχXN and g:=fχXN.

L1givenconstruct

Then gng everywhere, and g is measurable because f is. So [L1] gives gndμgdμ.

2.1

Each difference fngn=fnχN and fg=fχN is supported on the null set N.

step 1.1L2L3

Therefore [L2] and [L3] give

fndμ=gndμ,fdμ=gdμ.

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

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

Chebyshev-Markov inequality for the integral

Statement

Let f:X[0,+] be measurable and let t>0. Then μ({ft})1tfdμ.

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).

Proof

technique · direct
1.1

If E:={ft}, then tχEf. Applying [L1] gives[L1, given] tμ(E)=tχEdμfdμ.

2.1

Dividing by the positive number t yields[step 1.1, algebra] ∎ μ({ft})t1fdμ.

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

Integrable real and complex functions, and their integrals

Definition

Let f:XR 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 fdμ is +, in which case fdμ:=f+dμfdμ. The function is integrable when both integrals are finite, equivalently when fdμ<+.

For a complex measurable function h=u+iv with u=Reh, v=Imh (Real and imaginary parts, complex conjugation, and modulus), define h to be integrable when h is integrable, and then define hdμ:=udμ+ivdμ.

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:XC: 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=αfdμ+βgdμ(α,βC, f,gL1(μ)).

Facts & Assumptions

Given: Integrable functions f,gL1(μ) and scalars α,βC.

[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
1.1

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

L1L2L3L4algebra
1.2

Now let cR and let f be real-valued. By [L4], cf is measurable. If c0, 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=cfdμ.

L1L3L4algebra
2.1

Let h=u+ivL1(μ) and γ=a+ibC. Then γh=(aubv)+i(av+bu). The real-valued functions aubv and av+bu are integrable by steps 1.1 and 1.2, and their real-linear integral formulas combine into (γh)dμ=γhdμ. 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=h1dμ+ik1dμ+h2dμ+ik2dμ=αfdμ+βgdμ.

L1step 1.1step 1.2algebra
TheoremStatement: Literature-sourcedProof: AI-generatedprecheck passaudited 2026-08-27Open item page →

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

Statement

Let f,gL1(μ). Then the following are equivalent:

  1. f=g almost everywhere;
  2. for every measurable A, Afdμ=Agdμ.

For integrable real or complex h, the notation in condition 2 means Ahdμ:=hχAdμ; the product is integrable because hχAh.

Facts & Assumptions

Given: Integrable functions f,gL1(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
1.1

Assume f=g almost everywhere, with exceptional null set N. Then for [L1, L2, L4, given] every measurable A, the real and imaginary parts of (fg)χA are supported on N, so [L1] and [L2] give A(fg)dμ=0, hence Afdμ=Agdμ.

1.2

Assume instead that Afdμ=Agdμ for every measurable [L2, L3, L4, given] A. Apply this to the real part u:=Re(fg) on the set 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(fg) shows v=0 almost everywhere. Hence f=g almost everywhere.

2.1

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

step 1.1step 1.2
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 fL1(μ), then fdμfdμ.

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
1.1

For real-valued f, the functions f+f=2f+ and ff=2f are nonnegative. Therefore [L1] and [L4] give 0(f+f)dμ=fdμ+fdμ, 0(ff)dμ=fdμfdμ. So fdμfdμfdμ, and hence fdμfdμ.

L1L3L4algebra
2.1

For complex-valued f, let I:=fdμ. If I=0 there is nothing to prove. Otherwise set α:=I/I, so α=1 by [L2]. Then I=αI=αfdμ, 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)dμαfdμ=fdμ, because Rezz for every complex z.

L1L2step 1.1L4algebra
TheoremStatement: Literature-sourcedProof: AI-generatedprecheck passaudited 2026-08-27Open item page →

Dominated convergence

Statement

Let f and (fn) be measurable complex-valued functions such that fnf almost everywhere and fng almost everywhere for a single nonnegative measurable function g with gdμ<+. Then fL1(μ), fnfdμ0, and hence fndμfdμ.

Facts & Assumptions

Given: Measurable complex-valued functions f,fn with fnf almost everywhere and fng 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
1.1

Let N0 be a measurable null set outside which fn(x)f(x) and fn(x)g(x), and let N:={g=}. By [L6], the set N is null. Put N:=N0N, E:=XN, g~:=gχE,hn:=fnfχE. Then hn0 pointwise, 0hn2g~, and g~ is nonnegative, measurable, and finite everywhere. Also ffχN+g~. By [L5] and [L7], fdμfχNdμ+g~dμ=0+g~dμgdμ<+, so fL1(μ) by [L4].

L4L5L6L7given
2.1

The functions hn are nonnegative, converge pointwise to 0, and are dominated by the finite everywhere majorant 2g~. Applying [L1] therefore gives lim supnhndμ0dμ=0. Hence hndμ0.

step 1.1L1
3.1

Because fnfχN is supported on the null set N, [L5] gives fnfdμ=hndμ+fnfχNdμ=hndμ0. Therefore, by [L2] and [L3], fndμfdμ=(fnf)dμfnfdμ, and the right-hand side tends to 0.

step 1.1step 2.1L2L3L5
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 fnf almost everywhere. If fnM almost everywhere for one real M0, then fndμfdμ.

Facts & Assumptions

Given: A finite measure space, measurable complex-valued functions f,fn with fnf almost everywhere, and a uniform bound fnM.

[L1]

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

Proof

technique · direct
1.1

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

givenalgebra
2.1

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

step 1.1L1
TheoremStatement: Literature-sourcedProof: AI-generatedprecheck passaudited 2026-08-27Open item page →

Integrable simple functions are dense in L1(μ)

Statement

For every fL1(μ) there is a sequence of integrable simple functions (sn) such that fsndμ0.

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
1.1

Suppose first that f is real-valued. Choose simple unf+ and vnf by [L1], and put sn:=unvn. Then sn is an integrable simple function and fsn=(f+un)+(fvn)0, with fsnf. By [L3], fsndμ0.

L1L2L3construct
2.1

For complex f=u+iv, apply step 1.1 separately to u and v to obtain real simple functions pn,qn with upndμ0,vqndμ0. Set sn:=pn+iqn. Then sn is a simple integrable function and fsnupn+vqn. By [L4], fsndμupndμ+vqndμ0, so (sn) converges to f in L1.

step 1.1L2L4
TheoremStatement: Literature-sourcedProof: AI-generatedprecheck passaudited 2026-08-27Open item page →

Absolute continuity of the integral

Statement

Let fL1(μ) and let ε>0. Then there is δ>0 such that for every measurable E, μ(E)<δEfdμ<ε.

Facts & Assumptions

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

[L1]

The truncations fn increase pointwise to f, so their integrals converge to fdμ by monotone convergence (Monotone convergence for the integral).

[L2]

The integral over a measurable set is defined by Ehdμ=hχEdμ (Integral over a measurable subset).

[L3]

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

[L4]

Integrability means fdμ<+ (Integrable real and complex functions, and their integrals).

Proof

technique · direct
1.1

Choose n so large that [L1, L4, choose] (ffn)dμ<ε/2, which is possible by [L1] and [L4]. Put δ:=ε/(2n+1).

2.1

If μ(E)<δ, then [step 1.1, L2, L3, algebra] ∎ EfdμE(fn)dμ+(ffn)dμnμ(E)+ε/2<ε, using [L2] and [L3] for the first term.

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 fL1(μ) and νf(A):=fχAdμ(AA), then νf is countably additive on pairwise disjoint measurable families. Here fχA is integrable because fχAf; this formula defines the notation Afdμ for integrable real or complex f.

Facts & Assumptions

Given: An integrable function f.

[L1]

For every nonnegative measurable h, the set function AAhdμ 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 fL1(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 IR be an interval and let f:X×IC be such that:

  1. for every tI, the function xf(x,t) is integrable;
  2. for almost every x, the map tf(x,t) is continuous on I;
  3. there is a nonnegative measurable function g with gdμ<+ and f(x,t)g(x) for every tI 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
1.1

Fix t0I and let (tn) be any sequence in I with tnt0. For almost every x, continuity in t gives f(x,tn)f(x,t0), and the dominating bound gives f(x,tn)g(x).

givenL1
2.1

Apply [L1] to the sequence xf(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.

step 1.1L1
TheoremStatement: Literature-sourcedProof: AI-generatedprecheck passaudited 2026-08-27Open item page →

Differentiation under the integral sign

Statement

Let IR be an open interval and let f:X×IC be such that:

  1. for every tI, the function xf(x,t) is integrable;
  2. for almost every x, the map tf(x,t) is differentiable on I;
  3. for every tI, the function xft(x,t) is measurable;
  4. there are a measurable null set N and a nonnegative measurable function g with gdμ<+ and ft(x,t)g(x) for every tI and every xXN.

Then F(t):=f(x,t)dμ(x) is differentiable on I, and F(t)=ft(x,t)dμ(x).

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.

[L1]

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

Proof

technique · direct
1.1

Fix t0I and let hn0 with hn0 and t0+hnI. Define qn(x):=f(x,t0+hn)f(x,t0)hn. For every xXN, differentiability in t gives qn(x)tf(x,t0).

givenconstruct
2.1

For each n, hypothesis 1 makes xf(x,t0+hn) and [step 1.1, L1, L2] xf(x,t0) integrable and therefore measurable, so qn is measurable. Fix xXN 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 ⁣(αf(x,t0+hn)f(x,t0)hn). Apply [L2] to the real-valued function τRe(αf(x,τ)) on the segment joining t0 to t0+hn. For some interior point ξ of that segment, qn(x)=Re(αtf(x,ξ))tf(x,ξ)g(x). Hypothesis 3 makes xtf(x,t0) measurable. Therefore [L1] applies to (qn).

step 1.1L1L2
3.1

By [L1], limnqn(x)dμ(x)=tf(x,t0)dμ(x). But qn(x)dμ(x)=F(t0+hn)F(t0)hn, so the difference quotients of F converge to the displayed integral. Hence F is differentiable at t0 with the stated derivative.

step 2.1L1algebra
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 fL1(P) be real-valued, let IR be an interval containing f(x) for almost every x, and let φ:IR be convex with φfL1(P). Then φ ⁣(fdP)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:IR with φfL1(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
1.1

Put m:=fdP. If m lies in the interior of I, apply [L3] to obtain a supporting line (x)=φ(m)+a(xm) with (x)φ(x) on I. Integrating and using [L1] and [L2] gives φ(f)dP(f)dP=φ(m)+a(fdPm1dP)=φ(m).

L1L2L3givenalgebra
1.2

Suppose instead that m is an endpoint of I, say the left endpoint. Then [L1, L2, L4, given] fm0 almost everywhere and (fm)dP=fdPm1dP=0 by [L1] and [L2]. Therefore f=m almost everywhere by [L4], so φ(f)dP=φ(m)=φ ⁣(fdP). 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 fndμfdμ.

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).

2.1

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

step 1.1L1algebra
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 infnfndμ=lim infnfndμ.

Facts & Assumptions

Given: The statement above.

[L1]

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

Refutation

technique · direct
1.1

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

givenconstruct
2.1

Therefore lim infnfndμ=0, while fndμ=1 for every n. So the equality in the Statement fails, and [L1] is strict here.

step 1.1L1algebra
False statementConstruction: AI-adaptedVerification: AI-generatedprecheck passaudited 2026-08-27Open item page →

FALSE: dominated convergence holds without a dominating function

Statement

If fnf almost everywhere and each fn is integrable, then fndμfdμ.

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 fn0 almost everywhere and every fn is integrable.

2.1

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

step 1.1L1algebra
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 fdμ=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 fdλ=0.

1.2

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

step 1.1L1
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 kN.

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 fdμ+gdμ 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
1.1

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

givenconstruct
2.1

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

step 1.1L1algebra
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 ⁣(fdμ)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 fd#=2,φ(f)d#=2.

2.1

Therefore [step 1.1, L1, algebra] ∎ φ ⁣(fd#)=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