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15 results · all verified · 4 also independently AI-judged
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Lebesgue-Stieltjes Measures and Distribution Functions

1 · Prerequisites

2 · Summary

An increasing right-continuous function determines a finitely additive interval set function on the half-open algebra, and the Caratheodory extension theorem upgrades that data to a Borel measure on the line. The page then runs the construction in reverse: a Borel measure finite on compact sets yields a normalized distribution function, and the two constructions agree modulo constants.

With that dictionary in place, the standard interval formulas, point-mass formula, regularity, and canonical examples become transparent. Lebesgue measure appears as the identity distribution function, the Cantor function produces the singular atomless Cantor measure, and every finite Borel measure splits into its atomic and atomless parts.

3 · Logical flowchart

4 · Definitions, theorems and proofs

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

This page uses the nondecreasing, right-continuous, (a,b]-interval convention

This page fixes the convention

μF((a,b])=F(b)F(a)

for a nondecreasing, right-continuous function F:RR. That pairing of monotonicity, interval shape, and continuity direction is the one used in Folland and Hunter, and it is the one for which the shrinking intervals (a,a+1/n] force right continuity through continuity from above.

Another standard convention in the literature uses the left-continuous data [a,b) instead. The two choices are both legitimate, but they are not the same construction for a fixed function. This page adopts the former convention once, records the latter here only as a warning, and thereafter uses the left-limit notation F(a) of The left and right limits of f at c, as limits of the restrictions of f to A(,c) and A(c,) only in derived interval formulas. Throughout this page, the order hypothesis on F is the weak one F(x)F(y) for xy.

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

A Borel measure on R that is finite on compact sets

Definition

A Borel measure on R finite on compact sets is a measure

μ:B(R)[0,+]

on the Borel sigma-algebra The Borel sigma-algebra of a topological space such that

μ(K)<+for every compact KR.

This is the one-dimensional finiteness hypothesis used throughout the Lebesgue-Stieltjes correspondence on this page.

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

The algebra of finite disjoint unions of half-open intervals in R with extended endpoints

Definition

Call an h-interval any interval of one of the four forms

(,b],(a,b],(a,),R,

where a<b are real in the bounded case. Let H be the family of subsets ER for which there are a natural number m and pairwise disjoint h-intervals I1,,Im such that

E=i=1mIi.

The empty set is included as the empty union. This family is called the half-open interval algebra on R.

Every h-interval is an interval in the sense of Intervals of R: the nine order-convex forms, nondegeneracy, and length, and the complement in R of one h-interval is empty, another h-interval, or a disjoint union of two h-intervals. Intersections of h-intervals are h-intervals or empty, so finite disjoint unions of h-intervals are closed under complements, finite unions, and finite intersections. Therefore H is an algebra of subsets of R in the sense of Algebras of subsets.

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

The interval set function attached to a nondecreasing right-continuous function

Definition

Let F:RR be nondecreasing and right-continuous, and adopt the (a,b] convention of This page uses the nondecreasing, right-continuous, (a,b]-interval convention.

For a single h-interval I, define

μ0,F((a,b]):=F(b)F(a),

μ0,F((a,)):=supt>a(F(t)F(a)),

μ0,F((,b]):=supt<b(F(b)F(t)),

μ0,F(R):=supa<b(F(b)F(a)).

For a set EH presented as a finite disjoint union E=i=1mIi of h-intervals, define

μ0,F(E):=i=1mμ0,F(Ii),

with μ0,F():=0 for the empty union.

The same set can have more than one disjoint h-interval presentation, so the value needs a well-definedness proof. That is exactly the content of The Stieltjes interval set function is finitely additive on the half-open interval algebra , recorded here in justified_by.

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

The Stieltjes interval set function is finitely additive on the half-open interval algebra

Statement

Let F:RR be nondecreasing and right-continuous, and let μ0,F be the set function of The interval set function attached to a nondecreasing right-continuous function. Then the value of μ0,F(E) is independent of the chosen finite disjoint decomposition of EH. Moreover, if E,GH are disjoint, then

μ0,F(EG)=μ0,F(E)+μ0,F(G).

So μ0,F is a finitely additive set function on the half-open interval algebra.

Facts & Assumptions

Given: A nondecreasing right-continuous function F:RR and the set function μ0,F defined from finite disjoint unions of h-intervals.

[L1]

For every disjoint presentation E=i=1mIi in the half-open interval algebra, the proposed value is μ0,F(E)=i=1mμ0,F(Ii). (The interval set function attached to a nondecreasing right-continuous function)

Proof

technique · direct
1.1

Suppose E=i=1mIi=j=1nJj are two finite disjoint h-interval decompositions of the same set.

givenL1

Collect every finite endpoint appearing among the Ii and Jj, and adjoin or + when a left or right ray occurs. This gives an increasing list p0<<pr such that each Ii and each Jj is a disjoint union of consecutive h-cells C:=(p1,p], with the first or last cell possibly a ray.

2.1

If I is one interval from either decomposition, the sum of the μ0,F-values of the consecutive cells inside I telescopes to μ0,F(I).

step 1.1L1algebra

In the unbounded cases this is exactly the truncation/supremum convention built into The interval set function attached to a nondecreasing right-continuous function. Thus each decomposition gives the same total, namely the sum of the cell values over those C contained in E. So μ0,F(E) is well defined. [step 1.1, L1, algebra]

3.1

Let E,GH be disjoint, and choose disjoint h-interval decompositions of E and of G.

step 2.1givenalgebra

Refine them to a common endpoint grid as in step 1.1, and sum over the grid cells. The cells belonging to EG are exactly the disjoint union of the cells belonging to E and the cells belonging to G, so the corresponding cell sums add:

μ0,F(EG)=μ0,F(E)+μ0,F(G).

Together with step 2.1 this proves the claim. [step 2.1, given, algebra] ∎

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

The Stieltjes interval set function is a premeasure

Statement

Let F:RR be nondecreasing and right-continuous, and let μ0,F be the set function of The interval set function attached to a nondecreasing right-continuous function. Then μ0,F is a premeasure on the half-open interval algebra in the sense of Premeasures on algebras of sets.

Facts & Assumptions

Given: A nondecreasing right-continuous function F:RR, the associated interval set function μ0,F, a pairwise disjoint sequence (En)nN in the half-open interval algebra, and a set E=nNEn that also lies in the half-open interval algebra.

[L1]

The set function μ0,F is well defined and finitely additive on the half-open interval algebra. (The Stieltjes interval set function is finitely additive on the half-open interval algebra)

[L2]

Every closed bounded interval [a,b] is compact. (Heine-Borel by bisection: every closed bounded interval [a,b] is compact)

Proof

technique · direct
1.1

By [L1], it is enough to prove countable additivity when E is a single h-interval.

L1givenalgebra

Indeed, if E=r=1mIr is a finite disjoint union of h-intervals, then each EnIr is again a finite disjoint union of h-intervals, the families (EnIr)n are pairwise disjoint, and Ir=n(EnIr). Applying the single-interval case to each Ir and summing finitely gives the general case.

2.1

Let E=nIn be a disjoint union of h-intervals, with E itself an h-interval.

step 1.1L1givenalgebra

For every NN,

n=0Nμ0,F(In)=μ0,F ⁣(n=0NIn)μ0,F(E),

because E is the disjoint union of n=0NIn and the remainder En=0NIn, whose μ0,F-value is nonnegative. Hence nμ0,F(In)μ0,F(E). [step 1.1, L1, given, algebra]

3.1

Assume first that E=(a,b]=nNIn, where the In are pairwise disjoint h-intervals.

step 2.1L1givenalgebra

Let ε>0. Right continuity at a gives δ>0 with F(a+δ)F(a)<ε/2. For each n, if In meets [a+δ,b] then its right endpoint is finite; write that endpoint as vn, let un be its left endpoint, and choose wn>vn with F(wn)F(vn)<ε2n2. Then the open intervals (un,wn) cover [a+δ,b]: every x in that compact interval belongs to nIn=(a,b], hence lies in some In that must have finite right endpoint and therefore satisfies x(un,wn). [given, L2, choose]

4.1

By compactness from [L2], finitely many of those open intervals cover [a+δ,b].

step 3.1L1algebra

Write them as (un1,wn1),,(unm,wnm). Since (a+δ,b]j=1m(unj,wnj], monotonicity and finite additivity give

F(b)F(a+δ)j=1m(F(wnj)F(unj))<j=1mμ0,F(Inj)+ε2nμ0,F(In)+ε2.

Adding F(a+δ)F(a)<ε/2 yields

F(b)F(a)<nμ0,F(In)+ε.

[step 2.1, step 3.1, L1, algebra]

5.1

Because ε>0 was arbitrary, step 4.1 gives μ0,F((a,b])nμ0,F(In).

step 2.1step 4.1

Together with step 2.1, this proves countable additivity for bounded intervals. [step 2.1, step 4.1]

6.1

If E=(,b], then for every real M<b the bounded interval (M,b] is the disjoint union of the h-intervals In(M,b].

step 2.1step 5.1algebra

By step 5.1,

F(b)F(M)=nμ0,F(In(M,b])nμ0,F(In).

Taking the supremum over M<b gives μ0,F(E)nμ0,F(In). Combined with step 2.1, this proves countable additivity for left rays. The same argument with (a,M] proves the right-ray case E=(a,). [step 2.1, step 5.1, algebra]

7.1

If E=R, then for every real M<N the bounded interval (M,N] is the disjoint union of the h-intervals In(M,N].

step 2.1step 5.1step 6.1algebra

So step 5.1 gives

F(N)F(M)=nμ0,F(In(M,N])nμ0,F(In).

Taking the supremum over M<N yields μ0,F(R)nμ0,F(In). Together with step 2.1 and step 6.1, this proves countable additivity for every h-interval. [step 2.1, step 5.1, step 6.1, algebra]

8.1

By step 1.1, the single-interval cases of steps 5.1 through 7.1 imply the general countable additivity clause whenever a disjoint union in the algebra stays in the algebra.

step 1.1step 5.1step 6.1step 7.1

Therefore μ0,F is a premeasure. [step 1.1, step 5.1, step 6.1, step 7.1] ∎

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

Assuming countable choice, a nondecreasing right-continuous function defines a Borel measure on R

Statement

Assume the Axiom of Countable Choice. Let F:RR be nondecreasing and right-continuous. Then there is a Borel measure μF on R, finite on compact sets in the sense of A Borel measure on R that is finite on compact sets, such that

μF((a,b])=F(b)F(a)for all a<b.

Facts & Assumptions

Given: Countable choice, a nondecreasing right-continuous function F:RR, and its interval set function μ0,F on the half-open interval algebra.

[L1]

The interval set function μ0,F is a premeasure on the half-open interval algebra. (The Stieltjes interval set function is a premeasure)

[L2]

Assuming countable choice, a premeasure extends to a measure on the sigma-algebra it generates. (Assuming countable choice, a premeasure extends through its induced outer measure)

[L3]

The family of half-open intervals (a,b] with a<b generates the Borel sigma-algebra B(R). (Seven generating families for the Borel sigma-algebra on the real line)

[L4]

A compact subset of R is bounded. (A compact subset of R is closed and bounded)

Proof

technique · direct
1.1

By [L1], μ0,F is a premeasure, so [L2] gives a measure μ on the generated sigma-algebra σ(H) extending μ0,F.

L1L2L3

By [L3], that sigma-algebra is B(R), and therefore

μ((a,b])=μ0,F((a,b])=F(b)F(a)

for every a<b. [L1, L2, L3]

2.1

Let KR be compact. By [L4] there is R>0 with K[R,R](R1,R].

step 1.1L4algebra

So monotonicity and step 1.1 give

μ(K)μ((R1,R])=F(R)F(R1)<+.

Thus μ is finite on compact sets. [step 1.1, L4, algebra]

3.1

The measure μ of steps 1.1 and 2.1 is therefore a Borel measure on R finite on compact sets and having the prescribed half-open interval values.

step 1.1step 2.1

This is the required μF. [step 1.1, step 2.1] ∎

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

The interval data on (a,b] determines the Borel measure uniquely

Statement

Let μ and ν be Borel measures on R finite on compact sets in the sense of A Borel measure on R that is finite on compact sets. If

μ((a,b])=ν((a,b])for every a<b,

then μ(E)=ν(E) for every Borel set ER.

Facts & Assumptions

Given: Two Borel measures μ,ν on R, each finite on compact sets, and agreement of μ and ν on every half-open interval (a,b].

[L1]

The family of half-open intervals (a,b] with a<b generates the Borel sigma-algebra on R. (Seven generating families for the Borel sigma-algebra on the real line)

[L2]

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

Proof

technique · direct
1.1

Let

L1algebra

P:={(a,b]:a<b}.

If I1=(a,b] and I2=(c,d] lie in P, then I1I2 is either empty or another half-open interval (max{a,c},min{b,d}], so P is a pi-system. By [L1], σ(P)=B(R). [L1, algebra]

1.2

For each nN, put Pn:=(n1,n]P. The [given, algebra] sequence (Pn) is increasing and nPn=R. Because each Pn is contained in the compact interval [n1,n], both μ(Pn) and ν(Pn) are finite; and by the hypothesis they are equal.

givenalgebra
2.1

Step 1.1 provides the generating pi-system and step 1.2 provides the [step 1.1, step 1.2, L2] increasing finite-measure exhaustion. Therefore [L2] applies and yields μ=ν on B(R).

step 1.1step 1.2L2
DefinitionDefinition: Literature-sourcedProof: Not applicablejudge pass (gpt-5.6-terra)audited 2026-08-27Open item page →

The distribution function of a Borel measure on R, normalized at 0

Definition

Let μ be a Borel measure on R finite on compact sets. Its distribution function normalized at 0 is the function Fμ:RR defined by

Fμ(x):={μ((0,x]),x0,μ((x,0]),x<0.

Both interval measures are finite: the relevant half-open interval is contained in the closed bounded interval with endpoints 0 and x, which is compact by Heine-Borel by bisection: every closed bounded interval [a,b] is compact, and measure monotonicity Measures are monotone applies.

The two cases agree at x=0, where both give 0. This normalization removes the additive-constant ambiguity that would remain if one used only interval increments.

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

Assuming countable choice, finite-on-compacts Borel measures on R correspond to nondecreasing right-continuous functions modulo constants

Statement

Assume the Axiom of Countable Choice. Let μ be a Borel measure on R finite on compact sets, and let Fμ be its normalized distribution function from The distribution function of a Borel measure on R, normalized at 0. Then:

  1. Fμ is nondecreasing and right-continuous;

  2. for every a<b,

    Fμ(b)Fμ(a)=μ((a,b]);

  3. the Lebesgue-Stieltjes measure attached to Fμ is exactly μ.

Conversely, if F,G:RR are nondecreasing and right-continuous, then μF=μG if and only if FG is constant on R.

Facts & Assumptions

Given: Countable choice, a Borel measure μ on R finite on compact sets, its distribution function Fμ, and two nondecreasing right-continuous functions F,G:RR.

[L1]

Measures are continuous from above when one set in the decreasing chain has finite measure. (Continuity from above when one set has finite measure)

[L3]

Assuming countable choice, every nondecreasing right-continuous function defines a Borel measure on R with the prescribed values on half-open intervals. (Assuming countable choice, a nondecreasing right-continuous function defines a Borel measure on R)

[L4]

A Borel measure finite on compact sets is uniquely determined by its values on half-open intervals (a,b]. (The interval data on (a,b] determines the Borel measure uniquely)

Proof

technique · direct
1.1

The function Fμ is nondecreasing.

givenalgebra

If 0x<y, then (0,x](0,y], so Fμ(x)Fμ(y). If x<y0, then (y,0](x,0], so μ((x,0])μ((y,0]), again giving Fμ(x)Fμ(y). If x<0y, then Fμ(y)Fμ(x)=μ((0,y])+μ((x,0])=μ((x,y])0. [given, algebra]

1.2

Suppose first that μF=μG. Then for every a<b,

L3algebra

0=μF((a,b])μG((a,b])=(F(b)G(b))(F(a)G(a)).

So F(b)G(b)=F(a)G(a) for all a<b, and therefore FG is constant. [algebra]

1.3

Conversely, if FG is constant, then F(b)F(a)=G(b)G(a) for every a<b.

algebra
2.1

For every a<b one has Fμ(b)Fμ(a)=μ((a,b]).

step 1.1givenalgebra

In the three sign cases:

μ((0,b])μ((0,a])=μ((a,b])(0a<b),

μ((b,0])+μ((a,0])=μ((a,b])(a<b0),

and

μ((0,b])+μ((a,0])=μ((a,b])(a<0b).

So the displayed interval formula always holds. [step 1.1, given, algebra]

3.1

The function Fμ is right-continuous. Fix xR and let hn0 with hn>0.

step 2.1L1

For all large n one has x+hn<0 when x<0, while for x0 no sign change occurs. In either case, step 2.1 gives

Fμ(x+hn)Fμ(x)=μ((x,x+hn]).

The sets (x,x+hn] decrease to , and the first one has finite measure because it is contained in a compact interval. Therefore [L1] gives μ((x,x+hn])0, so Fμ(x+hn)Fμ(x). [step 2.1, L1]

4.1

By [L3], the function Fμ determines a Lebesgue-Stieltjes measure μFμ.

step 2.1step 3.1L3

Step 2.1 says that μFμ and μ agree on every half-open interval, so [L4] gives μFμ=μ. [step 2.1, step 3.1, L3, L4]

The interval values of μF and μG therefore agree by [L3], and [L4] yields μF=μG. Together with steps 1.1, 1.2, 1.3, 2.1, and 3.1 this proves the theorem. [step 1.1, step 1.2, step 1.3, step 2.1, step 3.1, L3, L4] ∎

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

An atom of a measure on R

Definition

Let μ be a Borel measure on R, that is, a measure in the sense of Measures on sigma-algebras on the Borel sigma-algebra The Borel sigma-algebra of a topological space. A point aR is an atom of μ when

μ({a})>0.

Equivalently, μ has a point mass at a.

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

Interval formulas and atoms for a Lebesgue-Stieltjes measure

Statement

Assume the Axiom of Countable Choice. Let F:RR be nondecreasing and right-continuous, and let μF be its Lebesgue-Stieltjes measure. Then for every a<b,

μF((a,b))=F(b)F(a),

μF([a,b])=F(b)F(a),

μF([a,b))=F(b)F(a),

and

μF({a})=F(a)F(a).

Consequently a is an atom of μF in the sense of An atom of a measure on R if and only if F(a)>F(a), and the set of atoms of μF is at most countable.

Facts & Assumptions

Given: The Axiom of Countable Choice, a nondecreasing right-continuous function F:RR, its Lebesgue-Stieltjes measure μF, and real numbers a<b.

[L1]

Assuming Countable Choice, the measure μF satisfies μF((u,v])=F(v)F(u) for all u<v. (Assuming countable choice, finite-on-compacts Borel measures on R correspond to nondecreasing right-continuous functions modulo constants)

[L2]

Measures are continuous from below along increasing set limits; they are continuous from above along decreasing set limits when one set has finite measure (Continuity from below for measures, Continuity from above when one set has finite measure).

[L3]

For a bounded-variation function on a compact interval, every well-posed one-sided limit exists, every discontinuity is of the first kind, and there are at most countably many discontinuities (A bounded-variation function has at most countably many discontinuities, all of the first kind).

[L4]

Assuming Countable Choice, a countable union of at most countable sets is at most countable (Countable unions of at most countable sets, assuming ACω).

[L5]

A point x is an atom of a Borel measure μ exactly when μ({x})>0 (An atom of a measure on R).

[L6]

If AB are measurable and μ(B)<+, then μ(BA)=μ(B)μ(A) (Measure of a set difference when the smaller set has finite measure).

Proof

technique · direct
1.1

Put tn:=b(ba)/(n+2). Then a<tn<b for every n and tnb.

L1L2L3algebra

Because (a,b)=n(a,tn], continuity from below and [L1] give

μF((a,b))=limnμF((a,tn])=limn(F(tn)F(a))=F(b)F(a).

Here F[a,b] has bounded variation because it is nondecreasing, so [L3] ensures that the displayed left limit exists. [L1, L2, L3, algebra]

2.1

Put sn:=a1/(n+1). Then sn<a and sna, while the intervals (sn,b] decrease to [a,b].

step 1.1L1L2L3

The first interval has finite measure because F is real-valued, so continuity from above and [L1] give

μF([a,b])=limnμF((sn,b])=limn(F(b)F(sn))=F(b)F(a).

The restriction F[a1,a] has bounded variation because it is nondecreasing, so [L3] ensures that the displayed left limit exists. [L1, L2, L3, algebra]

3.1

The intervals (sn,a] decrease to {a}, and continuity from above gives μF({a})=F(a)F(a).

step 2.1L1L2L3

Indeed, (s0,a] has finite measure and μF({a})=limnμF((sn,a])=limn(F(a)F(sn))=F(a)F(a). [step 2.1, L1, L2, L3]

The same argument gives μF({b})=F(b)F(b). Therefore

μF([a,b))=μF([a,b])μF({b})=F(b)F(a).

Together with step 1.1, this proves all four interval formulas. [step 1.1, step 2.1, step 3.1, L1, L6, algebra]

4.1

By step 3.1 and [L5], the point a is an atom of μF exactly when μF({a})=F(a)F(a)>0, which is exactly the jump condition F(a)>F(a).

step 3.1L5
5.1

Fix m1. The restriction F[m,m] is nondecreasing, hence of bounded variation on [m,m].

step 4.1L3

So [L3] makes its discontinuity set at most countable. Every atom of μF in (m,m) is an interior jump point by step 4.1, hence lies in that countable discontinuity set. Therefore the atoms in (m,m) are at most countable. By [L4], their union over m1 is at most countable, and this union contains every atom of μF. [given, step 4.1, L3, L4]

6.1

Steps 1.1 through 5.1 prove the claimed interval formulas, the atom criterion, and the countability of the atom set.

step 1.1step 2.1step 3.1step 4.1step 5.1

[step 1.1, step 2.1, step 3.1, step 4.1, step 5.1] ∎

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

Lebesgue-Stieltjes measures on R are outer regular and inner regular by compact sets

Statement

Let F:RR be nondecreasing and right-continuous, and let μF be the associated Lebesgue-Stieltjes measure. Then for every Borel set ER,

μF(E)=inf{μF(U):EU, U open}=sup{μF(K):KE, K compact}.

If μF(E)<+, then equivalently: for every ε>0 there are an open set U and a compact set K with

KEU,μF(UE)<ε,μF(EK)<ε.

Facts & Assumptions

Given: A nondecreasing right-continuous function F:RR, its Lebesgue-Stieltjes measure μF, a Borel set ER, and ε>0.

[L1]

The half-open interval formulas hold for μF, including the formulas for open and closed intervals. (Interval formulas and atoms for a Lebesgue-Stieltjes measure)

[L2]
[L3]

The half-open intervals generate the Borel sigma-algebra on R, and the monotone class generated by an algebra is the sigma-algebra it generates. (Seven generating families for the Borel sigma-algebra on the real line, The monotone class generated by an algebra equals the sigma-algebra it generates)

[L5]

The Borel sigma-algebra of a subspace is the trace of the ambient Borel sigma-algebra. (The Borel sigma-algebra of a subspace is the trace of the ambient Borel sigma-algebra)

Proof

technique · direct
1.1

Every bounded half-open interval is regular. Let I=(a,b].

L1L4choose

Choose η>0 so small that F((b+η))F(b)<ε; then the open interval U:=(a,b+η) contains I and [L1] gives

μF(UI)=μF((b,b+η))<ε.

Likewise choose δ>0 with F((a+δ))F(a)<ε; then the closed interval K:=[a+δ,b] is compact by [L4], satisfies KI, and [L1] gives

μF(IK)=μF((a,a+δ))=F((a+δ))F(a)<ε.

[L1, L4, choose]

2.1

Fix m1 and write Im:=[m,m]. Let Om be the family of Borel subsets AIm such that for every ε>0 there is an open set UR with

step 1.1L3L5

AU,μF((UIm)A)<ε.

By step 1.1, every trace HIm with HH lies in Om. Those traces form an algebra on Im, because H is an algebra on R and traces preserve complements and finite unions. By [L5] together with the generator statement of [L3], they generate the Borel sigma-algebra of the subspace Im. [step 1.1, L3, L5]

3.1

The family Om is a monotone class. If AnA and AnOm, choose open UnAn with μF((UnIm)An)<ε2n1.

step 2.1L1L2

Then U:=nUn is open, contains A, and

(UIm)An((UnIm)An),

so μF((UIm)A)<ε. If instead AnA, then A0Im has finite measure by [L1], so [L2] gives μF(AnA)0; choose n with μF(AnA)<ε/2, then choose open UnAn with μF((UnIm)An)<ε/2. The open set Un contains A, and

μF((UnIm)A)μF((UnIm)An)+μF(AnA)<ε.

[step 2.1, L1, L2]

4.1

Step 3.1 makes Om a monotone class containing the algebra from step 2.1.

step 2.1step 3.1L3

Therefore [L3] gives that every Borel subset of Im lies in Om: every bounded Borel set is relatively outer regular inside a compact interval. [step 2.1, step 3.1, L3]

5.1

Let AIm be Borel. Apply step 4.1 to the Borel complement ImA in the subspace Im.

step 4.1L4

Choose open UImA with μF((UIm)(ImA))<ε. Put K:=ImU. Then K is closed in the compact interval Im, hence compact by [L4], and KA. Moreover

AK=AU=(UIm)(ImA),

so μF(AK)<ε. Thus every bounded Borel set is also inner regular by compact sets. [step 4.1, L4]

6.1

The global inner regularity follows by truncation. Put Em:=EIm.

step 5.1L2algebra

Then EmE, so [L2] gives μF(E)=supmμF(Em). For each m, step 5.1 gives a compact KmEmE with μF(EmKm)<1/(m+1). Hence

sup{μF(K):KE, K compact}supmμF(Km)=supmμF(Em)=μF(E),

while the reverse inequality is monotonicity. [step 5.1, L2, algebra]

7.1

For global outer regularity, first suppose μF(E)<+. Choose m so large that μF(EIm)<ε/3.

step 4.1step 6.1L1L2

This is possible directly from [L2] on EImE. Step 4.1 gives an open VEIm with μF((VIm)E)<ε/3. For each of the two tails E(m,) and E(,m), decompose into unit half-open strips and apply step 4.1 on each compact strip, choosing the errors summably below ε/3; enlarging each strip by a thin open shell whose μF-measure is also chosen summably below ε/3 via [L1], the union of those stripwise open sets is open and contributes total excess below 2ε/3. Taking the union with V gives an open set UE with μF(UE)<ε. [step 4.1, step 6.1, L1, L2]

8.1

If μF(E)=+, then every open UE also has μF(U)=+ by monotonicity.

step 6.1step 7.1algebra

So inf{μF(U):EU, U open}=+=μF(E). Combining this with step 7.1 gives the outer regularity equality in all cases. The inner regularity equality is step 6.1, and the finite-measure ε-approximation statement is exactly the combination of steps 6.1 and 7.1. [step 6.1, step 7.1, algebra] ∎

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

Lebesgue measure is the Lebesgue-Stieltjes measure of the identity function

Statement

Assume the Axiom of Countable Choice. Let idR(x):=x. The Lebesgue-Stieltjes measure attached to idR agrees with Lebesgue measure λ from Lebesgue measurable sets, the family L(Rn), and the restricted set function λn on every Borel subset of R.

Facts & Assumptions

Given: Countable choice and the identity function idR:RR.

[L1]

Assuming countable choice, every nondecreasing right-continuous function on R defines a Borel measure through the Lebesgue-Stieltjes construction. (Assuming countable choice, a nondecreasing right-continuous function defines a Borel measure on R)

[L2]

For every half-open interval (a,b]R, Lebesgue measure satisfies λ((a,b])=ba. (A box in Rn with parameters aibi is Lebesgue measurable of measure i<n(biai), whichever of its faces are included)

[L3]

A Borel measure on R finite on compact sets is uniquely determined by its values on half-open intervals. (The interval data on (a,b] determines the Borel measure uniquely)

Proof

technique · direct
1.1

The identity function is nondecreasing and right-continuous, so [L1] gives a Borel measure μid with

L1

μid((a,b])=idR(b)idR(a)=ba.

[L1]

1.2

By [L2], Lebesgue measure has the same half-open interval values: λ((a,b])=ba for every a<b.

L2
2.1

The measures μid and λ are both Borel and finite on compact sets, and by steps 1.1 and 1.2 they agree on every half-open interval.

step 1.1step 1.2L3

Therefore [L3] gives μid=λ. [step 1.1, step 1.2, L3] ∎

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

The Cantor measure

Definition

Assume the Axiom of Countable Choice. Let c:[0,1]R be the Cantor function The Cantor function on [0,1], defined on the Cantor set through ternary digits and extended constantly across each removed interval. Define

Fc(x):={0,x<0,c(x),0x1,1,x>1.

By The Cantor function is well defined, satisfies c(x)c(y) whenever xy, is surjective onto [0,1], and is constant on every interval removed from the Cantor set and The Cantor function is continuous on [0,1], the function Fc is nondecreasing and right-continuous on R. The Cantor measure is the Lebesgue-Stieltjes measure

μc:=μFc

given by Assuming countable choice, a nondecreasing right-continuous function defines a Borel measure on R.

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

The Cantor measure is a singular atomless probability measure concentrated on the Cantor set

Statement

Assume the Axiom of Countable Choice. Let μc be the Cantor measure of The Cantor measure and let C[0,1] be the Cantor set. Then:

  1. μc([0,1])=1, so μc is a probability measure;
  2. μc({x})=0 for every xR, so μc is atomless;
  3. μc(RC)=0, so μc is concentrated on the Cantor set;
  4. since λ(C)=0, the measure μc is singular with respect to Lebesgue measure.

Facts & Assumptions

Given: The Axiom of Countable Choice, the Cantor function c, its extension Fc, the Cantor measure μc=μFc, and the Cantor set C.

[L2]

The interval and singleton formulas hold for every Lebesgue-Stieltjes measure. (Interval formulas and atoms for a Lebesgue-Stieltjes measure)

[L3]

Assuming Countable Choice, the Cantor set has Lebesgue measure zero. (The Cantor set is an uncountable subset of R of Lebesgue measure zero)

[L4]

Measures are continuous from below. (Continuity from below for measures)

Proof

technique · direct
1.1

By [L2],

L1L2

μc([0,1])=Fc(1)Fc(0)=10=1.

Likewise, for every n1, μc((1,n])=Fc(n)Fc(1)=0 and μc((n,0))=Fc(0)Fc(n)=0. So all mass lies in [0,1], and μc is a probability measure. [L1, L2]

2.1

If x(0,1], then [L1] makes Fc(x)=Fc(x), so [L2] gives [step 1.1, L1, L2] μc({x})=0. The same holds for x<0 and x>1 because Fc is constant on (,0) and on (1,), and it holds at x=0 because Fc(0)=Fc(0)=0. Hence μc is atomless.

step 1.1L1L2
3.1

Every point of [0,1]C lies in a complementary gap (u,v) of [step 2.1, L1, L2, L4, algebra] C, and [L1] makes c constant on [u,v]. Therefore [L2] gives

μc((u,v))=Fc(v)Fc(u)=c(v)c(u)=0.

Because [0,1]C is the countable union of those disjoint gaps, countable additivity gives μc([0,1]C)=0. Together with step 1.1 this yields μc(RC)=0. [step 2.1, L1, L2, L4, algebra]

4.1

By [L3], λ(C)=0, while step 3.1 shows that μc is concentrated [step 1.1, step 2.1, step 3.1, L3] on C. That is exactly the statement that μc is singular with respect to Lebesgue measure.

step 1.1step 2.1step 3.1L3
5.1

Steps 1.1 through 4.1 prove the probability, atomless, concentration, and [step 1.1, step 2.1, step 3.1, step 4.1] singularity claims.

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

Every finite Borel measure on R splits as an atomic part plus an atomless part

Statement

Assume the Axiom of Countable Choice. Let μ be a finite Borel measure on R. Then there are a countable set AR and a finite atomless Borel measure ν such that

μ=aAμ({a})δa+ν.

The set A is exactly the set of atoms of μ.

Facts & Assumptions

Given: The Axiom of Countable Choice and a finite Borel measure μ on R.

[L1]

Assuming Countable Choice, finite-on-compacts Borel measures correspond to increasing right-continuous distribution functions, and the resulting Lebesgue-Stieltjes measure is the original measure. (Assuming countable choice, finite-on-compacts Borel measures on R correspond to nondecreasing right-continuous functions modulo constants)

[L2]

For a Lebesgue-Stieltjes measure, atoms are exactly positive jumps, and there are at most countably many of them. (Interval formulas and atoms for a Lebesgue-Stieltjes measure)

[L3]

Every Dirac measure is a probability measure, and countable nonnegative weighted sums of measures are measures. (A Dirac set function is a probability measure, Nonnegative scalar multiples and countable weighted sums of measures are measures)

Proof

technique · direct
1.1

Let Fμ be the distribution function of μ. By [L1], one has μ=μFμ. Therefore [L2] shows that the atom set.

L1L2choose

A:={xR:μ({x})>0}

is at most countable. If A=, then μ({x})=0 for every xR, so μ is already atomless; taking ν:=μ proves the theorem. Otherwise choose an injective enumeration A={ai:iI}, where I={1,,m} if A is finite and I=N if A is infinite.

2.1

By [L3], the weighted Dirac sum

step 1.1L3algebra

μat:=iIμ({ai})δai

is a Borel measure. For every Borel set E,

μat(E)=aiEμ({ai})=μ(EA),

because the singletons {ai} are pairwise disjoint and countable additivity of μ applies to their union. [step 1.1, L3, algebra]

3.1

Define

step 2.1givenalgebra

ν(E):=μ(EA)(EB(R)).

Because (EnA) remains pairwise disjoint whenever (En) is, the same countable additivity as for μ shows that ν is a finite Borel measure. [step 2.1, given, algebra]

4.1

For every Borel set E, the disjoint decomposition E=(EA)(EA) gives.

step 2.1step 3.1algebra

μ(E)=μ(EA)+μ(EA)=μat(E)+ν(E).

If xA, then ν({x})=μ()=0; if xA, then μ({x})=0 by definition of A, so also ν({x})=0. Hence ν is atomless. [step 2.1, step 3.1, algebra]

5.1

If A=, step 1.1 already gives the claimed decomposition. Otherwise step 4.1 is exactly that decomposition, and step 1.1 identifies A as the atom set of μ.

step 1.1step 4.1

5 · Examples, counterexamples and false statements

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

FALSE: every nondecreasing function defines a Lebesgue-Stieltjes measure on Borel sets

Statement

False claim. Every nondecreasing function F:RR defines a Borel measure satisfying μ((a,b])=F(b)F(a). The valid construction on this page also requires the right-continuity recorded in This page uses the nondecreasing, right-continuous, (a,b]-interval convention.

Facts & Assumptions

Given: The function

F(x):={0,x0,1,x>0.

[L1]

Measures are continuous from above on decreasing measurable sets when one set in the chain has finite measure. (Continuity from above when one set has finite measure)

Refutation

technique · direct
1.1

The function F is nondecreasing but not right-continuous at 0: one has F(0)=0 while F(x)=1 for every x>0.

given

If a Borel measure μ satisfied μ((a,b])=F(b)F(a) for every a<b, then

μ((0,1/n])=F(1/n)F(0)=1

for every n1. [given]

2.1

The sets (0,1/n] decrease to , and μ((0,1])=F(1)F(0)=1<+.

step 1.1L1

Therefore [L1] would force

μ((0,1/n])μ ⁣(n=1(0,1/n])=μ()=0,

contradicting step 1.1. So no such measure exists. [step 1.1, L1] ∎

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

FALSE: a Lebesgue-Stieltjes measure always gives every singleton measure 0

Statement

False claim. Every Lebesgue-Stieltjes measure μF satisfies μF({a})=0 for every aR. In fact singleton masses are exactly the jumps of F by Interval formulas and atoms for a Lebesgue-Stieltjes measure.

Facts & Assumptions

Given: The Axiom of Countable Choice and the step function

F(x):={0,x<0,1,x0.

[L1]

For a Lebesgue-Stieltjes measure, one has μF({a})=F(a)F(a). (Interval formulas and atoms for a Lebesgue-Stieltjes measure)

[L2]

Assuming Countable Choice, every nondecreasing right-continuous real function defines a Lebesgue-Stieltjes measure. (Assuming countable choice, a nondecreasing right-continuous function defines a Borel measure on R)

Refutation

technique · direct
1.1

The function F is nondecreasing and right-continuous, so [L2] defines its [given, L2] Lebesgue-Stieltjes measure μF. At the point 0, one has F(0)=1 and F(0)=0.

2.1

Applying [L1] at a=0 gives

step 1.1L1

μF({0})=F(0)F(0)=1.

So the singleton {0} has positive measure, and the claim is false. [step 1.1, L1] ∎

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

FALSE: a Lebesgue-Stieltjes measure determines its distribution function uniquely

Statement

False claim. A Lebesgue-Stieltjes measure determines a unique distribution function. The valid statement on this page is only uniqueness modulo additive constants, with normalization at 0 choosing one representative.

Facts & Assumptions

Given: Countable choice, a nondecreasing right-continuous function F:RR, and the shifted function G:=F+1.

[L1]

Assuming countable choice, two nondecreasing right-continuous functions define the same Lebesgue-Stieltjes measure exactly when their difference is constant. (Assuming countable choice, finite-on-compacts Borel measures on R correspond to nondecreasing right-continuous functions modulo constants)

Refutation

technique · direct
1.1

The function G is nondecreasing and right-continuous whenever F is, and [given] GF is the constant function 1.

given
2.1

Therefore [L1] gives μG=μF. Unless F already equals F+1, [step 1.1, L1] which no real-valued function does, the two distribution functions are distinct. So the measure does not determine a unique representative without a normalization convention.

step 1.1L1
False statementConstruction: AI-adaptedVerification: AI-adaptedprecheck passaudited 2026-08-27Open item page →

FALSE: every Borel measure on R is finite on compact sets

Statement

False claim. Every Borel measure on R is finite on compact sets. The finiteness-on-compacts hypothesis in the Lebesgue-Stieltjes correspondence is therefore a genuine hypothesis, not a consequence of being a Borel measure.

Facts & Assumptions

Given: Counting measure #R on R.

[L1]

Counting measure is a measure on (R,P(R)). (Counting measure is a measure)

[L2]

Counting measure assigns an infinite set the value +. (Counting measure on an arbitrary set)

Refutation

technique · direct
1.1

By [L1], counting measure restricts to a Borel measure on R. The [L1, given] compact interval [0,1] is infinite.

L1given
2.1

Therefore [L2] gives [step 1.1, L2] #R([0,1])=+. So this Borel measure is not finite on the compact set [0,1], and the claim is false.

step 1.1L2
False statementConstruction: Literature-sourcedVerification: AI-adaptedprecheck passaudited 2026-08-27Open item page →

FALSE: every atomless Borel measure on R is absolutely continuous with respect to Lebesgue measure

Statement

False claim. Every atomless Borel measure on R has a density with respect to Lebesgue measure. The Cantor measure already separates atomlessness from absolute continuity.

Facts & Assumptions

Given: The Axiom of Countable Choice and the Cantor measure μc.

[L1]

Assuming Countable Choice, the Cantor measure is an atomless probability measure singular with respect to Lebesgue measure. (The Cantor measure is a singular atomless probability measure concentrated on the Cantor set)

Refutation

technique · direct
1.1

By [L1], the Cantor measure μc is atomless.

L1
2.1

The same fact [L1] says that μc is singular and has total mass 1. [step 1.1, L1] If it were absolutely continuous with respect to Lebesgue measure, its concentration on a Lebesgue-null set would force its total mass to be 0. Thus it is not absolutely continuous and cannot arise from a density. ∎

Sources