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20 results · all verified · 6 also independently AI-judged
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Measurable Functions and Simple Approximation

1 · Prerequisites

2 · Summary

Measurability is fixed first as a relation between two sigma-algebras, with the extended real line carrying its Borel sigma-algebra and real Euclidean targets carrying the usual Borel structure. From that point the page proves the three practical criteria used everywhere later: generators suffice, threshold sets suffice, and sequential suprema, infima, limsup, liminf, and pointwise limits preserve measurability.

The second half turns those abstract criteria into the approximation machinery used by integration. Nonnegative measurable functions admit explicit increasing simple approximants, general measurable functions admit dominated simple approximants, completion-measurable functions have base-measurable representatives, and the Doob-Dynkin lemma identifies exactly what it means for a function to be measurable with respect to the sigma-algebra generated by another one.

3 · Logical flowchart

4 · Definitions, theorems and proofs

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

Measurability is relative to sigma-algebras on both domain and codomain

In a measurable space Measurable spaces and measurable sets, the word measurable never belongs to a function by itself. It belongs to a function together with a source sigma-algebra and a target sigma-algebra. On this page the target on R or R is always the Borel sigma-algebra, not the Lebesgue sigma-algebra.

That convention is load-bearing. A Lebesgue measurable function on Rn means

f:(Rn,L(Rn))(Rm,B(Rm)),

not a map into (Rm,L(Rm)). The distinction is exactly what makes the later counterexample g \circ f with g merely Lebesgue measurable possible.

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

The Borel sigma-algebra on the extended real line

Definition

The extended real line is

R:=R{,+}

with the total order extending the usual order on R and satisfying <x<+ for every real x (The extended real line R=R{,+}, its order, and the arithmetic that is left undefined).

Its Borel sigma-algebra is the Borel sigma-algebra of that ordered topological line in the sense of The Borel sigma-algebra of a topological space. On this page it is denoted B(R) and is generated by the rays

{(a,+]:aR}.

In particular, {+} and {} are Borel sets.

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

A measurable function between measurable spaces

Definition

Let (X,A) and (Y,B) be measurable spaces (Measurable spaces and measurable sets). A function f:XY is measurable when

f1(B)Afor every BB.

Equivalently, the family

Cf:={BY:f1(B)A}

is a sigma-algebra on Y containing B.

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

An indicator function is measurable exactly when its set is measurable

Statement

Let (X,A) be a measurable space and let EX. The indicator function

1E(x):={1,xE,0,xE

is measurable as a map XR if and only if EA.

Facts & Assumptions

Given: A measurable space (X,A), a subset EX, and the indicator function 1E.

[L1]

A function is measurable exactly when the preimage of every measurable set in the codomain is measurable in the domain. (A measurable function between measurable spaces)

Proof

technique · direct
1.1

If EA, then the preimage of any Borel set B[given,L1]R under 1E is one of , X, E, or XE, because 1E takes only the values 0 and 1. Each of those sets lies in A, so 1E is measurable by [L1].

givenL1
1.2

If 1E is measurable, then

givenL1

E=1E1((1/2,)),

and (1/2,) is a Borel subset of R. Hence [L1] gives EA. [given, L1]

2.1

Steps 1.1 and 1.2 prove the equivalence.

step 1.1step 1.2
DefinitionDefinition: Literature-sourcedProof: Not applicableaudited 2026-08-27Open item page →

Borel measurable and Lebesgue measurable functions on Rn

Definition

Assume the Axiom of Countable Choice (The Axiom of Countable Choice (ACω)), so Assuming countable choice, L(Rn) is a sigma-algebra containing every elementary set and λn is a complete measure extending elementary volume makes L(Rn) a sigma-algebra. Let n,mN with n,m1.

When m=1, these are the corresponding notions for real-valued functions.

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

The positive and negative parts of a function

Definition

Let f:XR with R as in The extended real line R=R{,+}, its order, and the arithmetic that is left undefined. Its positive part and negative part are

f+:=max{f,0},f:=max{f,0}.

Pointwise, both functions take values in [0,+], and one has

f=f+f,f=f++f.

At each point at least one of f+ and f is zero.

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

A simple function and its canonical representation

Definition

Let (X,A) be a measurable space. A function s:XR is simple when it is measurable and its range is finite.

If the distinct values taken by s are c1,,cm, define

Ej:=s1({cj})(1jm).

Then the measurable sets E1,,Em are pairwise disjoint, their union is X, and

s=j=1mcj1Ej.

This expression is the canonical representation of s: the coefficients are the distinct values of s, and the sets are its level sets.

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

The sigma-algebra generated by a function

Definition

Let f:XY be a function and assume the target Y carries a Borel sigma-algebra B(Y).

The sigma-algebra generated by f is

σ(f):={f1(B):BB(Y)}.

Because preimages preserve complements and countable unions, this is a sigma-algebra on X. It is the smallest sigma-algebra on X that makes f measurable.

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

The convention 0=0 is used only for pointwise products of measurable functions

On this page the symbol fg for two R-valued measurable functions is a pointwise definition, not a limit rule. At points where one factor is 0 and the other is infinite, we set

0(+)=0()=0.

This convention exists only so that decompositions such as f=f+f and the measurable-product theorem stay pointwise total on the extended reals. It does not contradict Null times divergent has no rule: xk=1/k with yk=ck gives product limit c, and with yk=k2 gives divergence, because that counterexample concerns limits of ordinary real products, not the value of a pointwise formula.

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

A generating family on the codomain suffices to test measurability

Statement

Let (X,A) and (Y,B) be measurable spaces, let GP(Y) generate B, and let f:XY be a function. If

f1(G)Afor every GG,

then f is measurable as a map (X,A)(Y,B).

Facts & Assumptions

Given: Measurable spaces (X,A) and (Y,B), a function f:XY, and a generating family G for B.

[L1]

A function is measurable exactly when the preimage of every measurable set in the codomain is measurable in the domain. (A measurable function between measurable spaces)

Proof

technique · direct
1.1

Let

L1algebra

C:={BY:f1(B)A}.

Preimages preserve complements and countable unions, so C is a sigma-algebra on Y. [L1, algebra]

2.1

By hypothesis, every member of G lies in C. Since [given, step 1.1] B is the sigma-algebra generated by G, one has BC.

givenstep 1.1
3.1

Therefore f1(B)A for every BB, and [step 2.1, L1] [L1] says exactly that f is measurable.

step 2.1L1
TheoremStatement: Literature-sourcedProof: AI-adaptedprecheck passaudited 2026-08-27Open item page →

Threshold characterisations of real-valued and extended-real-valued measurability

Statement

Let (X,A) be a measurable space and let f:XR. The following are equivalent:

  1. f is measurable;
  2. {x:f(x)>a}A for every real a;
  3. {x:f(x)a}A for every real a;
  4. {x:f(x)<a}A for every real a;
  5. {x:f(x)a}A for every real a.

Moreover, in any one of conditions 2 through 5 it is enough to test only rational thresholds aQ.

Facts & Assumptions

Given: A measurable space (X,A) and a function f:XR.

[L1]

The Borel sigma-algebra on R is generated by the rays (a,+] with aR. (The Borel sigma-algebra on the extended real line)

[L2]

A generating family on the codomain suffices to test measurability. (A generating family on the codomain suffices to test measurability)

[L3]

Between any two distinct real numbers there lies a rational number. (The rationals embed densely in the reals)

Proof

technique · direct
1.1

By [L1], the threshold set {x:f(x)>a} is the preimage [L1, L2] f1((a,+]). Therefore [L2] gives the equivalence of condition 1 and condition 2.

L1L2
1.2

Suppose the sets {f>q} are measurable for every rational q. For a [L3, algebra] real a,

{fa}=X{f>a},{f<a}=X{fa}.

So conditions 2 and 5 are equivalent, and conditions 3 and 4 are equivalent. [step 1.1, algebra]

2.1

For every real a,

step 1.1algebra

{fa}=n=1{f>a1/n},{f>a}=n=1{fa+1/n},

so conditions 2 and 3 are equivalent. Combining this with steps 1.1 and 1.2 shows that conditions 1 through 5 are all equivalent. [step 1.1, step 1.2, algebra]

2.2

For every real a,

step 1.1algebra

{f>a}=qQ,q>a{f>q}.

Indeed, f(x)>q>a implies f(x)>a, and if f(x)>a then [L3] gives a rational q with a<q<f(x) unless f(x)=+, in which case any rational q>a works. Thus the real-threshold version of condition 2 follows from the rational one. The converse is immediate, so in condition 2 it is enough to test only rational thresholds. [L3, algebra]

3.1

The equivalences from steps 2.1 and 2.2 transfer the rational-threshold [step 2.1, step 2.2, step 1.2] reduction of step 1.2 to conditions 3 through 5. Therefore in any one of conditions 2 through 5 it is enough to test only rational thresholds.

step 2.1step 2.2step 1.2
CorollaryStatement: Literature-sourcedProof: AI-adaptedprecheck passaudited 2026-08-27Open item page →

Continuous functions on Euclidean spaces are Borel measurable

Statement

Assume the Axiom of Countable Choice. Let n,m1. Every continuous map f:RnRm is Borel measurable in the sense of Borel measurable and Lebesgue measurable functions on Rn.

Facts & Assumptions

Given: The Axiom of Countable Choice, natural numbers n,m1, and a continuous function f:RnRm.

[L1]

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

Proof

technique · direct
1.1

Let BRm be Borel. By [L1], the preimage [L1] f1(B) is a Borel subset of Rn.

L1
2.1

By the definition of Borel measurability on Euclidean spaces, step 1.1 says [step 1.1] exactly that f is Borel measurable.

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

Every monotone real function is Borel measurable

Facts & Assumptions

Given: A monotone function f:RR.

[L1]

A real-valued function is measurable exactly when all of its threshold sets {x:f(x)>a} are measurable. (Threshold characterisations of real-valued and extended-real-valued measurability)

Proof

technique · direct
1.1

Suppose first that f is increasing. For each real a, the threshold set [given] Ea:={x:f(x)>a} is upward closed: if xEa and y>x, then f(y)f(x)>a, so yEa. Therefore Ea is one of the four Borel sets , R, (c,), or [c,) for some real c.

given
2.1

Every set named in step 1.1 is Borel, so [L1] gives that every increasing [step 1.1, L1, algebra] real function is measurable. If f is decreasing, then f is increasing and hence measurable by the first half, and therefore f is measurable as well.

step 1.1L1algebra
TheoremStatement: Literature-sourcedProof: AI-adaptedprecheck passaudited 2026-08-27Open item page →

A map into Rn is measurable exactly when its coordinates are measurable

Statement

Let n1, let (X,A) be a measurable space, and let f=(f1,,fn):XRn. Then f is measurable if and only if each coordinate function fj:XR is measurable.

Facts & Assumptions

Given: A natural number n1, a measurable space (X,A), and a function f=(f1,,fn):XRn.

[L2]

A generating family on the codomain suffices to test measurability. (A generating family on the codomain suffices to test measurability)

[L3]

Real-valued measurability is equivalent to threshold measurability. (Threshold characterisations of real-valued and extended-real-valued measurability)

Proof

technique · direct
1.1

Suppose f is measurable. Fix j and a real a. Then

L3given

{x:fj(x)>a}=f1 ⁣(Rj1×(a,)×Rnj).

The displayed strip is open, hence Borel in Rn, so the preimage is measurable. By [L3], each coordinate fj is measurable. [L3, given]

1.2

Conversely, suppose every coordinate fj is measurable. Let [L1, L3, algebra] B=j=1n(aj,bj) be a rational open box. Then

f1(B)=j=1n{x:aj<fj(x)<bj},

and each factor on the right is measurable by [L3]. Therefore f1(B)A for every rational open box B. [L1, L3, algebra]

2.1

By [L1] and [L2], step 1.2 implies that f is measurable. Together with [step 1.1, step 1.2, L1, L2] step 1.1, this proves the equivalence.

step 1.1step 1.2L1L2
TheoremStatement: Literature-sourcedProof: AI-adaptedprecheck passjudge pass (gpt-5.6-terra)audited 2026-08-27Open item page →

Composition with a Borel measurable outer map preserves measurability

Statement

Let (X,A), (Y,B), and (Z,C) be measurable spaces. If f:(X,A)(Y,B) is measurable and g:(Y,B)(Z,C) is measurable, then gf:(X,A)(Z,C) is measurable.

In particular, if f is measurable and g is a Borel measurable function on its codomain, then gf is measurable.

Facts & Assumptions

Given: Measurable spaces (X,A), (Y,B), (Z,C), a measurable map f:XY, and a measurable map g:YZ.

[L1]

Measurability means that preimages of measurable sets are measurable. (A measurable function between measurable spaces)

Proof

technique · direct
1.1

Let CC. Since g is measurable, [L1] gives [given, L1] g1(C)B.

givenL1
2.1

Since f is measurable, [L1] applied again gives

step 1.1L1

(gf)1(C)=f1(g1(C))A.

So gf is measurable. [step 1.1, L1] ∎

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

Arithmetic and lattice operations preserve measurability whenever they are defined

Statement

Let (X,A) be a measurable space and let f,g:XR be measurable. Then:

  1. cf is measurable for every real scalar c;
  2. max(f,g), min(f,g), f, f+, and f are measurable;
  3. if f+g is pointwise defined, then f+g is measurable;
  4. with the convention of The convention 0=0 is used only for pointwise products of measurable functions, the pointwise product fg is measurable.

Facts & Assumptions

Given: A measurable space (X,A) and measurable functions f,g:XR.

[L1]

Extended-real measurability is equivalent to measurability of the threshold sets {h>a}. (Threshold characterisations of real-valued and extended-real-valued measurability)

[L2]

The positive and negative parts are h+=max(h,0) and h=max(h,0). (The positive and negative parts of a function)

[A1]

In this proof, the pointwise product uses the page convention 0(+)=0()=0.

Proof

technique · direct
1.1

Scalar multiples are measurable. If c>0, then [given, L1] {cf>a}={f>a/c}; if c<0, then {cf>a}={f<a/c}; and if c=0, the function is constant. So [L1] gives measurability of cf, and in particular of f.

givenL1
2.1

The threshold identities

step 1.1L1L2

{max(f,g)>a}={f>a}{g>a},{min(f,g)>a}={f>a}{g>a}

show via [L1] that max(f,g) and min(f,g) are measurable. By [L2], this proves measurability of f+ and f; replacing g by f also gives f=max(f,f). [step 1.1, L1, L2]

3.1

Assume f+g is pointwise defined. For every real a,

step 2.1L1

{f+g>a}=qQ({f>q}{g>aq}).

The inclusion from right to left is immediate. For the converse, if f(x)+g(x)>a then either f(x)=+, in which case any rational q>ag(x) works, or f(x) is finite and one may choose a rational q with ag(x)<q<f(x). Thus [L1] gives measurability of f+g. [step 2.1, L1]

4.1

Suppose first that u,v:X[0,+] are nonnegative and measurable. [step 3.1, L1, A1] If a<0, then {uv>a}=X. If a0, then

{uv>a}=qQ,q>0({u>q}{v>a/q}).

Again the inclusion from right to left is immediate. For the converse, if u(x)v(x)>a, choose a rational q with 0<q<u(x) and a/q<v(x); this is possible because either u(x) is finite positive and the rationals are dense, or u(x)=+, in which case any sufficiently large positive rational works. Hence nonnegative products are measurable by [L1]. [step 3.1, L1, A1]

5.1

For general measurable f and g, step 2.1 gives measurable nonnegative [step 2.1, step 3.1, step 4.1, L2, A1] functions f+,f,g+,g. By step 4.1 the four products f+g+,fg,f+g,fg+ are measurable. Put

h+:=f+g++fg,h:=f+g+fg+.

At each point, at least one of h+ and h is zero, because at least one of f+,f and at least one of g+,g is zero. So the difference h+h is pointwise defined without the forbidden form, and step 3.1 makes it measurable. By the usual sign decomposition, h+h=fg, with the convention [A1] at the 0 points. [step 2.1, step 3.1, step 4.1, L2, A1]

6.1

Steps 1.1 through 5.1 prove all four claims.

step 1.1step 2.1step 3.1step 4.1step 5.1
TheoremStatement: Literature-sourcedProof: AI-adaptedprecheck passaudited 2026-08-27Open item page →

Sequential suprema, infima, limsup, liminf, and pointwise limits of measurable functions are measurable

Statement

Let (X,A) be a measurable space and let fn:XR be measurable for every nN. Then the functions

supnfn,infnfn,lim supnfn,lim infnfn

are measurable. The set

{x:limnfn(x) exists in R}

is measurable. In particular, if fnf pointwise, then f is measurable.

Facts & Assumptions

Given: A measurable space (X,A) and measurable functions fn:XR for nN.

[L1]

Threshold measurability characterizes extended-real measurability. (Threshold characterisations of real-valued and extended-real-valued measurability)

[L2]

For each x, the limsup and liminf of the sequence (fn(x)) satisfy

lim supnfn(x)=infnsupknfk(x),lim infnfn(x)=supninfknfk(x),

Proof

technique · direct
1.1

Let s(x):=supnfn(x) and i(x):=infnfn(x). Then for every real [L1, given] a,

{s>a}=n{fn>a},{i>a}=qQ,q>a n{fn>q}.

Since each threshold set on the right is measurable, [L1] gives measurability of s and i. [L1, given]

2.1

For each n, the tail functions [step 1.1, L2] sn(x):=supknfk(x) and in(x):=infknfk(x) are measurable by step 1.1. Applying step 1.1 again to the sequences (sn) and (in) and then using [L2] yields measurability of lim supnfn and lim infnfn.

step 1.1L2
3.1

Let u:=lim supnfn and v:=lim infnfn. The equality set [step 2.1, L1, L2] {u=v} is measurable because

{u=v}=qQ(({u>q}{v>q})({uq}{vq})).

If u(x)<v(x) or v(x)<u(x), a rational strictly between them separates the two sides; if u(x)=v(x), every rational lies on the same side of both values. So [L2] makes the pointwise-convergence set measurable. [step 2.1, L1, L2]

4.1

If fnf pointwise, then [L2] gives [step 2.1, step 3.1, L2] f=lim supnfn=lim infnfn. Since step 2.1 has already proved that both limiting functions are measurable, f is measurable.

step 2.1step 3.1L2
TheoremStatement: Literature-sourcedProof: AI-adaptedprecheck passjudge pass (gpt-5.6-terra)audited 2026-08-27Open item page →

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

Statement

Let (X,A) be a measurable space and let f:X[0,+] be measurable. For kN define

sk:=j=0k2k1j2k1{j2kf<(j+1)2k}+k1{fk}.

Then each sk is a simple measurable function,

0sksk+1f,

and sk(x)f(x) for every xX. If EX is a set on which fM<+, then skf uniformly on E.

Facts & Assumptions

Given: A measurable space (X,A), a measurable function f:X[0,+], and the dyadic truncations sk displayed above.

[L1]

Threshold measurability characterizes measurable R-valued functions. (Threshold characterisations of real-valued and extended-real-valued measurability)

[L2]

A measurable real-valued function with finite range is simple, and its canonical representation is the sum over its level sets. (A simple function and its canonical representation)

Proof

technique · direct
1.1

For fixed k, each set [L1, L2] {j2kf<(j+1)2k} and {fk} is measurable by [L1]. Hence sk is a measurable real-valued function. Its values belong to the finite set {0,2k,22k,,(k2k1)2k,k}, so [L2] makes sk a simple function.

L1L2
1.2

Fix xX. If f(x)k, then sk(x)=kf(x) and also [given, algebra] sk+1(x)k=sk(x). If f(x)<k, choose j with j2kf(x)<(j+1)2k. Then sk(x)=j2kf(x) and f(x)sk(x)<2k. At the finer scale 2k1, the same point lies in one of the two adjacent dyadic cells over that coarse cell, so sk+1(x) is either j2k or j2k+2k1. Thus sk(x)sk+1(x)f(x).

givenalgebra
2.1

The inequalities of step 1.2 hold for every x, so [step 1.2] 0sksk+1f. If f(x)<+, then for all k>f(x) the second case of step 1.2 applies and gives 0f(x)sk(x)<2k, hence sk(x)f(x). If f(x)=+, then sk(x)=k for every k, so sk(x)+=f(x).

step 1.2
3.1

If fM<+ on a set E, then for every k>M the second case of [step 1.2, step 2.1] step 1.2 applies to every xE and gives 0f(x)sk(x)<2k. Therefore

supxEf(x)sk(x)2k,

so skf uniformly on E. [step 1.2, step 2.1] ∎

CorollaryStatement: AI-adaptedProof: AI-adaptedprecheck passaudited 2026-08-27Open item page →

Every measurable function admits simple approximations dominated by its absolute value

Statement

Let (X,A) be a measurable space and let f:XR be measurable. Then there is a sequence of simple functions sk:XR such that

skffor every k,

and sk(x)f(x) for every xX.

Facts & Assumptions

Given: A measurable function f:XR.

[L1]

The positive and negative parts satisfy f=f+f, f=f++f, and at each point at least one of f+,f is zero. (The positive and negative parts of a function)

[L2]

The arithmetic-and-lattice theorem makes f+ and f measurable. (Arithmetic and lattice operations preserve measurability whenever they are defined)

[L3]

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

Proof

technique · direct
1.1

By [L2], the functions f+ and f are measurable and nonnegative. Applying [L1, L2, L3] [L3] to them gives simple functions ukf+ and vkf.

L1L2L3
2.1

Put sk:=ukvk. Because uk and vk are simple, sk is a [step 1.1, L1] simple real-valued function. At each point, [L1] makes at least one of uk and vk equal to 0, so

sk=uk+vkf++f=f.

Also skf+f=f pointwise because ukf+ and vkf. [step 1.1, L1] ∎

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

On a complete measure space, equality almost everywhere preserves measurability

Statement

Let (X,A,μ) be a complete measure space, let f:XR be measurable, and let g:XR satisfy g=f almost everywhere. Then g is measurable.

Facts & Assumptions

Given: A complete measure space (X,A,μ), a measurable function f:XR, a function g:XR, and a measurable null set N such that f=g on XN.

[L1]

In a complete measure space, every subset of a measurable null set is measurable and null. (Null sets are closed under countable unions and, in a complete space, under arbitrary subsets)

[L2]

Threshold measurability characterizes measurable R-valued functions. (Threshold characterisations of real-valued and extended-real-valued measurability)

Proof

technique · direct
1.1

Fix a real a. On XN, the equality g=f gives

givenalgebra

{g>a}(XN)={f>a}(XN).

Therefore

{g>a}=({f>a}(XN))({g>a}N).

[given, algebra]

2.1

The set {f>a} is measurable by [L2]. The set {g>a}N is a [step 1.1, L1, L2] subset of the measurable null set N, so [L1] makes it measurable. Hence {g>a} is measurable for every real a.

step 1.1L1L2
3.1

By [L2], step 2.1 proves that g is measurable.

step 2.1L2
TheoremStatement: AI-adaptedProof: AI-adaptedprecheck passaudited 2026-08-27Open item page →

A function measurable for a completion is almost everywhere equal to one measurable for the original sigma-algebra

Statement

Assume the Axiom of Countable Choice. Let (X,A0,μ) be a measure space and let (X,A0,μ) be its completion. If f:XR is measurable with respect to A0, then there is an A0-measurable function g:XR such that f=g almost everywhere.

Facts & Assumptions

Given: The Axiom of Countable Choice, a measure space (X,A0,μ), its completion (X,A0,μ), and an A0-measurable function f:XR.

[L1]

Every measurable function admits simple approximations dominated by its absolute value. (Every measurable function admits simple approximations dominated by its absolute value)

[L2]

A completed measurable set has the form AN with AA0 and N contained in a measurable null set. (The completion domain and proposed completed set function of a measure space)

[L3]

Assuming Countable Choice, the completion is a complete measure space extending the original measure, and countable unions of completed null sets are completed null sets. (Assuming countable choice, every measure space has a unique complete extension to its completion, Null sets are closed under countable unions and, in a complete space, under arbitrary subsets)

[L4]

Pointwise limsup of a sequence of measurable functions is measurable. (Sequential suprema, infima, limsup, liminf, and pointwise limits of measurable functions are measurable)

Proof

technique · direct
1.1

By [L1], choose simple A0-measurable functions [L1, choose] sk:XR with skf and sk(x)f(x) for every xX. Write the canonical representation of sk as

sk=j=1mkck,j1Ek,j,

where the Ek,j are pairwise disjoint completed measurable level sets. [L1, choose]

1.2

For each pair (k,j), apply [L2] to Ek,j and choose [L2, L3, choose] Ak,jA0 together with a completed null set Nk,j such that Ek,j=Ak,jMk,j with Mk,jNk,j. Because Ak,jEk,j, the sets Ak,j remain pairwise disjoint. Define

tk:=j=1mkck,j1Ak,j.

Then each tk is A0-measurable and simple. Let N:=k,jNk,j. By [L3], N is a completed measurable null set, and for every xN one has tk(x)=sk(x) for all k. [L2, L3, choose]

2.1

Define

step 1.1step 1.2L4

g:=lim supktk.

By [L4], the function g is A0-measurable. If xN, then step 1.2 gives tk(x)=sk(x) for every k, and step 1.1 gives sk(x)f(x), so g(x)=lim supktk(x)=limksk(x)=f(x). Hence g=f on XN. [step 1.1, step 1.2, L4]

3.1

The null set N is measurable in the completion by [L3], so step 2.1 says [step 2.1, L3] exactly that f=g almost everywhere. Since g is A0-measurable, it is the required base-measurable representative.

step 2.1L3
TheoremStatement: Literature-sourcedProof: AI-adaptedprecheck passaudited 2026-08-27Open item page →

Doob-Dynkin factorization through the sigma-algebra generated by a function

Statement

Let f:XR and g:XR. Then g is σ(f)-measurable if and only if there is a Borel measurable function h:RR such that

g=hf.

Facts & Assumptions

Given: Functions f:XR and g:XR.

[L1]

The sigma-algebra generated by f is σ(f)={f1(B):BB(R)}. (The sigma-algebra generated by a function)

[L2]

Threshold measurability characterizes R-valued measurability. (Threshold characterisations of real-valued and extended-real-valued measurability)

Proof

technique · direct
1.1

If g=hf for a Borel measurable h, then for every Borel set [L1] BR,

(hf)1(B)=f1(h1(B))σ(f),

because h1(B) is Borel in R and [L1] describes exactly the sets whose preimages under f lie in σ(f). So g is σ(f)-measurable. [L1]

2.1

Conversely, assume g is σ(f)-measurable. For each rational [step 1.1, L1, L2, algebra] qQ, the threshold set {gq} lies in σ(f) by [L2], so [L1] provides a Borel set AqR with

{gq}=f1(Aq).

Define

Bq:=rQr>qAr.

Then each Bq is Borel, the family (Bq)qQ is increasing in q, and

{gq}=f1(Bq)

for every rational q, because {gq}=r>q, rQ{gr}. [L1, L2, algebra]

3.1

For yR, define

step 2.1L2

h(y):=inf{qQ:yBq},

with the infimum taken in R, so the empty-set case gives +. Because the sets Bq are increasing,

{y:h(y)q}=Bq(qQ),

so [L2] makes h Borel measurable. [step 2.1, L2]

4.1

Fix xX and write t:=g(x). If q<t is rational, then [step 2.1, step 3.1, L2] x{gq}=f1(Bq), so f(x)Bq and therefore h(f(x))>q. If qt is rational, then x{gq}=f1(Bq), so f(x)Bq and therefore h(f(x))q. Thus h(f(x)) is at once at least every rational below t and at most every rational above t, which forces h(f(x))=t=g(x).

step 2.1step 3.1L2
5.1

Steps 1.1 and 4.1 prove the two directions of the equivalence.

step 1.1step 4.1

5 · Examples, counterexamples and false statements

False statementConstruction: Literature-sourcedVerification: AI-adaptedprecheck passaudited 2026-08-27Open item page →

FALSE: if every level set of a real-valued function is measurable, then the function is measurable

Statement

False claim. If every level set {x:f(x)=a} of a real-valued function is measurable, then the function itself is measurable.

Facts & Assumptions

Given: The Axiom of Choice, the Lebesgue measurable-space structure on [0,1], and a Vitali set V[0,1].

[L2]

Assuming the Axiom of Choice, a Vitali set is not Lebesgue measurable. (Assuming the Axiom of Choice, a Vitali set is not Lebesgue measurable)

Refutation

technique · direct
1.1

Define f:[0,1]R by [given, L1] f(x)=x for xV and f(x)=x+2 for xV. Every level set of f is empty, a singleton, or a two-point set, hence measurable.

givenL1
2.1

The set f1([2,3]) is exactly V, because on [0,1]V the [step 1.1, L2] values lie in [0,1] and on V they lie in [2,3]. By [L2], the set V is not measurable, so f is not measurable.

step 1.1L2
False statementConstruction: Literature-sourcedVerification: AI-adaptedprecheck passjudge pass (gpt-5.6-terra)audited 2026-08-27Open item page →

FALSE: if the absolute value is measurable, then the function is measurable

Statement

False claim. If f is measurable, then f is measurable.

Facts & Assumptions

Given: The Axiom of Choice, the Lebesgue measurable-space structure on [0,1], and a Vitali set V[0,1].

[L1]

Assuming the Axiom of Choice, Vitali sets exist. (Assuming choice on the cosets of Q in R, a Vitali set in [0,1] exists)

[L2]

Assuming the Axiom of Choice, a Vitali set is not Lebesgue measurable. (Assuming the Axiom of Choice, a Vitali set is not Lebesgue measurable)

Refutation

technique · direct
1.1

Define f:[0,1]R by f=1 on V and f=1 on [given, L1] [0,1]V. Then f is the constant function 1, hence measurable.

givenL1
2.1

But

step 1.1L2

{x:f(x)>0}=V,

which is not measurable by [L2]. So f is not measurable even though f is. [step 1.1, L2] ∎

False statementConstruction: Literature-sourcedVerification: AI-adaptedprecheck passaudited 2026-08-27Open item page →

FALSE: the supremum of an arbitrary family of measurable functions is always measurable

Statement

False claim. The pointwise supremum of an arbitrary family of measurable functions is measurable. The correct theorem on this page is only the sequential version.

Facts & Assumptions

Given: The Axiom of Choice, the Lebesgue measurable-space structure on [0,1], a Vitali set V[0,1], and the family {1{t}:tV} of indicator functions on [0,1].

[L2]

The indicator of a measurable set is measurable. (An indicator function is measurable exactly when its set is measurable)

Refutation

technique · direct
1.1

Each singleton {t} is measurable, so [L2] makes every [given, L2] 1{t} measurable.

givenL2
2.1

The pointwise supremum of the family is

step 1.1L1L2

suptV1{t}=1V.

Since V is not measurable by [L1], the function 1V is not measurable. So an uncountable supremum of measurable functions can fail to be measurable. [step 1.1, L1, L2] ∎

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

FALSE: equality almost everywhere with a measurable function implies measurability

Statement

False claim. If g equals a measurable function almost everywhere, then g is measurable. This fails on incomplete measure spaces.

Facts & Assumptions

Given: The Axiom of Choice and the Borel measure space (R,B(R),λB(R)), the Cantor set C, and the homeomorphism ψ(x)=x+c(x) from [0,1] onto [0,2].

[L1]

The set K=ψ[C] is compact and has Lebesgue measure 1, so it has positive outer measure; every positive-outer-measure subset of R contains a nonmeasurable subset. (The homeomorphism xx+c(x) sends the Cantor set onto a compact set of Lebesgue measure 1, Every subset of R of positive Lebesgue outer measure contains a nonmeasurable subset)

[L3]

The map ψ is a homeomorphism from [0,1] onto [0,2]. (The map xx+c(x) is a homeomorphism from [0,1] onto [0,2])

Refutation

technique · direct
1.1

By [L1], choose a nonmeasurable subset NK, and put [L1, L2, L3, choose] E:=ψ1[N]C. Since EC and C is Lebesgue null, [L2] makes E Lebesgue measurable. If E were Borel, then continuity of ψ1K from [L3] would make N Borel in the subspace K, hence Lebesgue measurable, which contradicts the choice of N. So E is Lebesgue measurable but not Borel.

L1L2L3choose
2.1

Let f=0 and g=1E on R. The function f is Borel [step 1.1, L2] measurable, and g=f on RC, so g=f almost everywhere with respect to λB(R) because C is a measurable null set by [L2]. But

g1((1/2,))=E,

and E is not Borel by step 1.1, so g is not measurable on this incomplete measure space. [step 1.1, L2] ∎

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

FALSE: composing a Lebesgue measurable function with a continuous map preserves measurability

Statement

False claim. Let X,YR carry their trace Lebesgue sigma-algebras. If f:XY is continuous and g:YR is Lebesgue measurable, then gf is Lebesgue measurable.

Facts & Assumptions

Given: The Axiom of Choice, the Cantor set C, the homeomorphism ψ(x)=x+c(x) from [0,1] onto [0,2], and K:=ψ[C].

[L2]

The indicator of a measurable set is measurable. (An indicator function is measurable exactly when its set is measurable)

Refutation

technique · direct
1.1

Choose a nonmeasurable NK by [L1], put [L1, L2, choose] E:=ψ1[N]C, let g:=1E:[0,1]R, and let f:=ψ1:[0,2][0,1]. Completeness makes E Lebesgue measurable in R, hence measurable in the trace sigma-algebra on [0,1], so [L2] makes g measurable, while [L1] makes f continuous.

2.1

But

step 1.1L1

(gf)1((1/2,))=f1[E]=N,

which does not lie in the trace sigma-algebra L(R)[0,2], even though g is measurable and f is continuous. [step 1.1, L1] ∎

False statementConstruction: AI-adaptedVerification: AI-adaptedprecheck passjudge pass (gpt-5.6-terra)audited 2026-08-27Open item page →

FALSE: a pointwise limit of continuous functions is continuous almost everywhere

Statement

False claim. A pointwise limit of continuous functions on R is continuous almost everywhere.

Facts & Assumptions

Given: The fat Cantor set S[0,1].

[L1]

The fat Cantor set is closed, nowhere dense, and not Lebesgue null. (The Smith-Volterra-Cantor set is compact, perfect and nowhere dense, and does not have measure zero)

Refutation

technique · direct
1.1

By [L2], there is a continuous function u:RR with [L2, choose] S={x:u(x)=0}. Put f0:=f1, and for n1 define

fn(x):=11+nu(x)2.

Each fn is continuous, because it is built from u by continuous algebraic operations and the denominator is everywhere positive. [L2, choose]

2.1

If xS, then u(x)=0 and fn(x)=1 for every n. If xS, [step 1.1, L1] then u(x)2>0, so 1+nu(x)2+ and fn(x)0. Thus the pointwise limit is 1S. Since S is closed and has empty interior by [L1], every point of S is a boundary point of S, and the indicator 1S is discontinuous at every such point. Because S is not Lebesgue null by [L1], the discontinuity set has positive measure.

step 1.1L1

Sources