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TheoremStatement: Literature-sourcedProof: AI-generatedprecheck passjudge pass (gpt-5.6-terra)audited 2026-08-28
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Almost uniform convergence implies almost-everywhere convergence and convergence in measure

Statement

Let (X,A,μ) be a measure space and let fn,f:X→R be measurable. If fn→f almost uniformly, then fn→f μ-almost everywhere and fn→f in measure.

Facts & Assumptions

Given: A measure space (X,A,μ), measurable functions fn,f:X→R, and almost-uniform convergence of (fn) to f.

[L1]

Almost-uniform convergence means that for every ε>0 there is a measurable E with μ(E)<ε such that fn→f uniformly on X∖E. (Almost uniform convergence)

[L2]

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

[L3]

Convergence in measure means that for every real ε>0, μ({∣fn−f∣>ε})→0. (Convergence in measure)

[L4]

If A⊆B are measurable, then μ(A)≤μ(B). (Measures are monotone)

Proof

technique · direct
1.1L1L2L4

For each m≥1, [L1] gives a measurable set Em with μ(Em)<1/m such that fn→f uniformly on X∖Em. Let N:=⋂m=1∞Em. Since N⊆Em for every m, [L4] gives μ(N)≤1/m for every m, hence μ(N)=0. If x∈X∖N, then x∉Em for some m, and uniform convergence on X∖Em implies fn(x)→f(x). Therefore fn→f almost everywhere by [L2].

1.2L1L3L4

Fix ε>0 and η>0. By [L1] choose a measurable set E with μ(E)<η such that fn→f uniformly on X∖E. Then there is N such that for n≥N and x∈X∖E one has ∣fn(x)−f(x)∣≤ε, so {∣fn−f∣>ε}⊆E. Hence μ({∣fn−f∣>ε})≤μ(E)<η for n≥N. Since η was arbitrary, [L3] follows.

2.1step 1.1step 1.2∎

Steps 1.1 and 1.2 prove the two asserted conclusions.

Depends on

Used by

Dependency tree · two levels

8 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.

Sources