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8 results · all verified · 6 also independently AI-judged
Every result on this page is machine-checked by a proof checker and read in full and owner-audited; the judge is an additional, independent cross-model AI review of the proofs. The 2 not AI-judged were verified by owner audit (typically over a confirmed judge false positive), not failures.

Modes of Convergence Egorov and Lusin: Examples and Counterexamples

1 · Prerequisites

2 · Summary

The companion page carries the witnesses that make the implication diagram on the main page concrete. The typewriter sequence separates convergence in measure and in L1 from pointwise almost-everywhere convergence; the translated unit intervals show exactly where finite measure enters; the spike family separates convergence in measure from convergence in L1; and the Dirichlet-function and disjoint-spike examples keep the Lusin and uniform integrability traps visible instead of leaving them as prose.

3 · Logical flowchart

4 · Definitions, theorems and proofs

None yet.

5 · Examples, counterexamples and false statements

ExampleConstruction: Literature-sourcedVerification: AI-generatedprecheck passaudited 2026-08-28Open item page →

The typewriter sequence converges in measure and in L^1 but nowhere pointwise

Example

On [0,1] with Lebesgue measure, define f0:=0,f2k+j:=χIk,jfor k0, 0j<2k, where Ik,j=[j2k,(j+1)2k) for j<2k1 and Ik,2k1=[12k,1]. Then:

  1. fn0 in measure.
  2. fn0 in L1([0,1]).
  3. For every x[0,1], the sequence (fn(x)) does not converge.

So the typewriter sequence separates convergence in measure and in L1 from almost-everywhere convergence.

Facts & Assumptions

Given: Lebesgue measure on [0,1] and the typewriter sequence (fn) of the Example, including its initial value f0=0.

[L1]

Convergence in measure means that for every real ε>0, μ({fnf>ε})0. (Convergence in measure)

[L2]

Convergence in L1(μ) means fnfdμ0. (Convergence in L^1(mu))

[L3]

Almost-everywhere convergence means pointwise convergence off a measurable null set. (Convergence almost everywhere relative to a measure)

Verification

technique · direct
1.1

If 2kn<2k+1, then fn is the indicator of a dyadic interval of length 2k, so 01fndλ=2k.

givenL2algebra
1.2

Fix x[0,1]. In each generation k1 there is exactly one interval Ik,jk containing x, so f2k+jk(x)=1. The same generation also contains intervals missing x, hence infinitely many indices n with fn(x)=0. So (fn(x)) takes the values 0 and 1 infinitely often and therefore does not converge.

given
2.1

Since 2kn<2k+1 forces k as n, step 1.1 gives 01fndλ0. Therefore fn0 in L1([0,1]) by [L2].

step 1.1L2
2.2

Fix ε(0,1). When 2kn<2k+1, the set {fn0>ε} is exactly the support interval of fn, so it has measure 2k. Thus these bad-set measures tend to 0, and [L1] gives fn0 in measure.

step 1.1L1
3.1

Step 2.2 proves convergence in measure, step 2.1 proves convergence in L1, and step 1.2 shows that [L3] fails at every point.

step 1.2step 2.1step 2.2L3
ExampleConstruction: AI-generatedVerification: AI-generatedprecheck passjudge pass (gpt-5.6-terra)audited 2026-08-28Open item page →

The leftmost dyadic intervals give an explicit almost-everywhere Riesz subsequence

Example

For the typewriter sequence of The typewriter sequence converges in measure and in L^1 but nowhere pointwise, take the subsequence g0:=f1=χ[0,1],gk:=f2k=χ[0,2k)(k1).

Then gk0 on (0,1], fails only at 0, and in fact converges almost uniformly to 0.

Facts & Assumptions

Given: The typewriter sequence (fn) and its leftmost-interval subsequence gk:=f2k.

[L1]

The typewriter sequence is the sequence of dyadic interval indicators defined in The typewriter sequence converges in measure and in L^1 but nowhere pointwise.

[L2]

Convergence in measure has an almost-everywhere convergent subsequence. (Riesz's subsequence theorem for convergence in measure)

[L3]

On a finite measure space, convergence in measure has an almost-uniformly convergent subsequence. (On a finite measure space, convergence in measure has an almost-uniformly convergent subsequence)

Verification

technique · direct
1.1

By [L1], g0=f1=χ[0,1], and for k1 the index 2k picks the first dyadic interval of generation k, so gk=χ[0,2k).

L1
2.1

If x(0,1], choose K with 2K<x. Then for every kK one has x[0,2k), so gk(x)=0. Thus gk(x)0 for every x(0,1], while gk(0)=1 for all k.

step 1.1choosealgebra
2.2

Let ε>0, put δ:=min{ε/2,1/2}, and take E:=[0,δ). Then λ(E)=δ<ε, and if x[δ,1] and 2k<δ then gk(x)=0. So gk0 uniformly on [δ,1], which is almost-uniform convergence.

step 1.1choosealgebra
3.1

Step 2.1 exhibits an explicit almost-everywhere convergent subsequence of the typewriter family, matching the general existence promised by [L2], and step 2.2 strengthens it to almost-uniform convergence, matching [L3].

step 2.1step 2.2L2L3
CounterexampleConstruction: Literature-sourcedVerification: AI-generatedprecheck passjudge pass (gpt-5.6-terra)audited 2026-08-28Open item page →

The translates of the unit interval converge almost everywhere to zero but not in measure

Statement refuted

almost-everywhere convergence implies convergence in measure on every measure space.

Facts & Assumptions

Given: Lebesgue measure on R and the sequence fn:=χ[n,n+1].

[L1]

Almost-everywhere convergence means pointwise convergence off a measurable null set. (Convergence almost everywhere relative to a measure)

[L2]

Convergence in measure means that for every real ε>0, μ({fnf>ε})0. (Convergence in measure)

Counterexample

technique · direct
1.1

Fix xR. If n>x+1, then x[n,n+1], so fn(x)=0. Hence fn(x)0 for every xR, and therefore almost everywhere by [L1].

givenL1
1.2

For every n one has {fn0>1/2}=[n,n+1], whose Lebesgue measure is 1. So the bad-set measures do not tend to 0, and [L2] fails.

givenL2
2.1

This sequence satisfies the premise of the refuted statement and violates its conclusion.

step 1.1step 1.2
CounterexampleConstruction: AI-generatedVerification: AI-generatedprecheck passjudge pass (gpt-5.6-terra)audited 2026-08-28Open item page →

The translated unit intervals show that Egorov needs finite total measure

Statement refuted

Egorov's theorem holds on every measure space.

Facts & Assumptions

Given: Lebesgue measure on R and the sequence fn:=χ[n,n+1].

[L1]

This sequence converges almost everywhere to 0 but not in measure. (The translates of the unit interval converge almost everywhere to zero but not in measure)

[L2]

Almost-uniform convergence implies convergence in measure. (Almost uniform convergence implies almost-everywhere convergence and convergence in measure)

Counterexample

technique · direct
1.1

By [L1], the sequence fn=χ[n,n+1] converges almost everywhere to 0.

L1
2.1

If this convergence were almost uniform, then [L2] would force convergence in measure as well. But [L1] says that convergence in measure fails. So the convergence is not almost uniform.

L1L2discharge-contradiction
CounterexampleConstruction: Literature-sourcedVerification: AI-generatedprecheck passjudge pass (gpt-5.6-terra)audited 2026-08-28Open item page →

The spikes k chi_(0,1/k) converge almost everywhere and in measure to zero but not in L^1

Statement refuted

convergence in measure implies convergence in L1(μ).

Facts & Assumptions

Given: Lebesgue measure on [0,1] and the sequence defined by f0:=0 and fn(x):=nχ(0,1/n)(x) for n1.

[L1]

Almost-everywhere convergence means pointwise convergence off a measurable null set. (Convergence almost everywhere relative to a measure)

[L2]

Convergence in measure means that for every real ε>0, μ({fnf>ε})0. (Convergence in measure)

[L3]

Convergence in L1(μ) means fnfdμ0. (Convergence in L^1(mu))

Counterexample

technique · direct
1.1

Fix x[0,1]. If x>0, then 1/n<x for all large n, so fn(x)=0 eventually; and fn(0)=0 for every n. Thus fn(x)0 for every x[0,1], hence almost everywhere by [L1].

givenL1
1.2

Fix ε>0. For all n>ε one has {fn0>ε}=(0,1/n), whose measure is 1/n0. So fn0 in measure by [L2].

givenL2
1.3

For every n1, [given, L3, algebra] 01fndλ=01/nndλ=1. So the L1 errors from 0 never tend to 0, and [L3] fails.

2.1

The sequence converges almost everywhere and in measure to 0, but not in L1.

step 1.1step 1.2step 1.3
ExampleConstruction: AI-generatedVerification: AI-generatedprecheck passjudge pass (gpt-5.6-terra)audited 2026-08-28Open item page →

Egorov for x^k on the unit interval

Example

On [0,1] with Lebesgue measure, the functions fk(x):=xk converge pointwise to the function f(x)={0,0x<1,1,x=1.

For every ε(0,1), the exceptional set (1ε,1] has measure ε, and on the closed core [0,1ε] the convergence is uniform with estimate xkf(x)(1ε)k.

Facts & Assumptions

Given: Lebesgue measure on [0,1], the sequence fk(x):=xk, and ε(0,1).

[L1]

Egorov's theorem says that on a finite measure space, almost-everywhere convergence implies almost-uniform convergence. (Egorov's theorem)

Verification

technique · direct
1.1

If 0x<1, then xk0, while 1k=1 for every k. Thus fkf pointwise on [0,1].

given
2.1

Put E:=(1ε,1]. Then λ(E)=ε, and for x[0,1ε] one has f(x)=0 and fk(x)f(x)=xk(1ε)k. Since (1ε)k0, the convergence is uniform on [0,1ε].

step 1.1algebra
3.1

This is the almost-uniform conclusion predicted abstractly by [L1], and here the exceptional set and the uniform estimate are explicit.

step 2.1L1
ExampleConstruction: Literature-sourcedVerification: AI-generatedprecheck passaudited 2026-08-28Open item page →

The Dirichlet function satisfies Lusin's conclusion without being continuous anywhere

Example

Let D:=1Q[0,1] on [0,1]. Then for every ε>0 there is a closed set F[0,1] with λ([0,1]F)<ε such that DF is continuous, even though D is nowhere continuous on [0,1].

Facts & Assumptions

Given: The Dirichlet function D:=1Q[0,1] and a real ε>0.

[L1]

The rationals are countable. (Q is countably infinite)

[L2]

For measurable (Ek) one has μ(kEk)k=0μ(Ek). (Finite and countable subadditivity of measures)

[L3]

If AB are measurable, then λ(A)λ(B). (Measures are monotone)

[L5]

Verification

technique · direct
1.1

By [L1], enumerate the rationals in [0,1] as (qj)j1. For each j, choose an open interval Uj centred at qj with length below ε2j1, and put U:=j1Uj. Then Q[0,1]U, and [L2] gives λ(U)j=1λ(Uj)<ε.

L1L2choose
2.1

Put F:=[0,1]U. Since U is open, [L4] makes F closed, and F contains no rationals. Therefore DF=0, so the restriction is continuous. Also [0,1]F=U[0,1]U, so [L3] and step 1.1 give λ([0,1]F)λ(U)<ε.

step 1.1L3L4
3.1

By [L5], every neighbourhood of every point of [0,1] meets both Q and its complement, so D is nowhere continuous on [0,1]. Thus step 2.1 is about the restriction DF, not continuity of D at the points of F.

step 2.1L5
ExampleConstruction: AI-generatedVerification: AI-generatedprecheck passjudge pass (gpt-5.6-terra)audited 2026-08-28Open item page →

A uniformly integrable family need not admit a single integrable majorant

Example

On [0,1] with Lebesgue measure, define ak:=j=1k112j2,Ik:=[ak,ak+12k2),fk:=kχIk.

Then the family (fk)k1 is uniformly integrable, but no integrable function dominates all of it almost everywhere.

Facts & Assumptions

Given: Lebesgue measure on [0,1], the intervals Ik, and the functions fk:=kχIk.

[L1]

Uniform integrability means that for every ε>0 there is M>0 such that {fk>M}fkdμ<ε for every k. (A uniformly integrable family)

[L2]

On finite measure spaces, uniform integrability is equivalent to L1-boundedness plus uniform absolute continuity. (On a finite measure space, uniform integrability is equivalent to L^1-boundedness plus uniform absolute continuity)

Verification

technique · direct
1.1

The series k=112k2 converges to a value below 1, so the intervals Ik are pairwise disjoint subsets of [0,1]. Also fkdλ=kλ(Ik)=12k.

givenalgebra
2.1

If M>0 and kM, then {fk>M}=; if k>M, then {fk>M}=Ik and {fk>M}fkdλ=12k12M+2. Hence the family is uniformly integrable by [L1].

step 1.1L1algebra
2.2

If g were an integrable majorant for all fk, then ggk almost everywhere on Ik. Since the intervals are pairwise disjoint, gdλk=1Ikgdλk=112k=+, contradicting integrability of g.

step 1.1algebra
3.1

This family is therefore uniformly integrable but has no single integrable majorant. The example is exactly the failure of the false statement paired with [L2].

step 2.1step 2.2L2

Sources