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Modes of Convergence Egorov and Lusin: Examples and Counterexamples
1 · Prerequisites
- Binary Operations, Monoids, Groups and Subgroups
- Construction of the Natural Numbers
- Construction of the Real Numbers via Cauchy Sequences
- Construction of the Real Numbers via Dedekind Cuts
- Cosets, Index and Lagrange's Theorem
- Countability and Uncountability
- Divisibility, Euclidean Domains, Principal Ideal Domains and Unique Factorisation
- Finite Counting, Factorials and Binomial Coefficients
- Foundations of the Real Numbers for Analysis
- Ideals, Quotient Rings and the Isomorphism Theorems for Rings
- limsup, liminf, and Subsequential Limits
- Measures and Their Basic Properties
- Modes of Convergence Egorov and Lusin
- Monotone Sequences, Bolzano-Weierstrass, and Cauchy Completeness
- Normal Subgroups and Quotient Groups
- Order, Zorn's Lemma, and the Axiom of Choice
- Polynomial Rings, the Division Algorithm and Roots
- Relations, Functions, and Quotients
- Rings, Subrings, Integral Domains and Fields
- Roots, Rational Powers, and Classical Inequalities
- Sequences and Limits
- Sequences and Series of Functions; Uniform Convergence
- Sigma Algebras and Borel Sets
- Simple Field Extensions and the Construction of the Complex Numbers
- Suprema and Infima
- The Lebesgue Integral and the Convergence Theorems
- The ZFC Axioms and the Basic Set Constructions
- Topological Spaces and Continuity
- Topology of ℝ
- Vector Spaces, Linear Subspaces, Span and Direct Sums
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 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 ; 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
The typewriter sequence converges in measure and in L^1 but nowhere pointwise
Example
On with Lebesgue measure, define where for and . Then:
- in measure.
- in .
- For every , the sequence does not converge.
So the typewriter sequence separates convergence in measure and in from almost-everywhere convergence.
Facts & Assumptions
Given: Lebesgue measure on and the typewriter sequence of the Example, including its initial value .
Convergence in measure means that for every real , . (Convergence in measure)
Convergence in means . (Convergence in L^1(mu))
Almost-everywhere convergence means pointwise convergence off a measurable null set. (Convergence almost everywhere relative to a measure)
Verification
If , then is the indicator of a dyadic interval of length , so
Fix . In each generation there is exactly one interval containing , so . The same generation also contains intervals missing , hence infinitely many indices with . So takes the values and infinitely often and therefore does not converge.
Since forces as , step 1.1 gives . Therefore in by [L2].
Fix . When , the set is exactly the support interval of , so it has measure . Thus these bad-set measures tend to , and [L1] gives in measure.
Step 2.2 proves convergence in measure, step 2.1 proves convergence in , and step 1.2 shows that [L3] fails at every point.
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
Then on , fails only at , and in fact converges almost uniformly to .
Facts & Assumptions
Given: The typewriter sequence and its leftmost-interval subsequence .
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.
Convergence in measure has an almost-everywhere convergent subsequence. (Riesz's subsequence theorem for convergence in measure)
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
By [L1], , and for the index picks the first dyadic interval of generation , so
If , choose with . Then for every one has , so . Thus for every , while for all .
Let , put , and take . Then , and if and then . So uniformly on , which is almost-uniform convergence.
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].
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 and the sequence .
Almost-everywhere convergence means pointwise convergence off a measurable null set. (Convergence almost everywhere relative to a measure)
Convergence in measure means that for every real , . (Convergence in measure)
Counterexample
Fix . If , then , so . Hence for every , and therefore almost everywhere by [L1].
For every one has , whose Lebesgue measure is . So the bad-set measures do not tend to , and [L2] fails.
This sequence satisfies the premise of the refuted statement and violates its conclusion.
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 and the sequence .
This sequence converges almost everywhere to but not in measure. (The translates of the unit interval converge almost everywhere to zero but not in measure)
Almost-uniform convergence implies convergence in measure. (Almost uniform convergence implies almost-everywhere convergence and convergence in measure)
Counterexample
By [L1], the sequence converges almost everywhere to .
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.
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 .
Facts & Assumptions
Given: Lebesgue measure on and the sequence defined by and for .
Almost-everywhere convergence means pointwise convergence off a measurable null set. (Convergence almost everywhere relative to a measure)
Convergence in measure means that for every real , . (Convergence in measure)
Convergence in means . (Convergence in L^1(mu))
Counterexample
Fix . If , then for all large , so eventually; and for every . Thus for every , hence almost everywhere by [L1].
Fix . For all one has , whose measure is . So in measure by [L2].
For every , [given, L3, algebra] So the errors from never tend to , and [L3] fails.
The sequence converges almost everywhere and in measure to , but not in .
Egorov for x^k on the unit interval
Example
On with Lebesgue measure, the functions converge pointwise to the function
For every , the exceptional set has measure , and on the closed core the convergence is uniform with estimate .
Facts & Assumptions
Given: Lebesgue measure on , the sequence , and .
Egorov's theorem says that on a finite measure space, almost-everywhere convergence implies almost-uniform convergence. (Egorov's theorem)
Verification
If , then , while for every . Thus pointwise on .
Put . Then , and for one has and . Since , the convergence is uniform on .
This is the almost-uniform conclusion predicted abstractly by [L1], and here the exceptional set and the uniform estimate are explicit.
The Dirichlet function satisfies Lusin's conclusion without being continuous anywhere
Example
Let on . Then for every there is a closed set with such that is continuous, even though is nowhere continuous on .
Facts & Assumptions
Given: The Dirichlet function and a real .
The rationals are countable. ( is countably infinite)
For measurable one has . (Finite and countable subadditivity of measures)
If are measurable, then . (Measures are monotone)
A set is closed when its complement is open. (Open subset of (every point has a neighbourhood inside it), closed subset (complement open), and clopen)
Both the rationals and the irrationals are dense in . (Both and are dense in , and every nonempty open subset of is uncountable)
Verification
By [L1], enumerate the rationals in as . For each , choose an open interval centred at with length below , and put . Then , and [L2] gives
Put . Since is open, [L4] makes closed, and contains no rationals. Therefore , so the restriction is continuous. Also , so [L3] and step 1.1 give .
By [L5], every neighbourhood of every point of meets both and its complement, so is nowhere continuous on . Thus step 2.1 is about the restriction , not continuity of at the points of .
A uniformly integrable family need not admit a single integrable majorant
Example
On with Lebesgue measure, define
Then the family is uniformly integrable, but no integrable function dominates all of it almost everywhere.
Facts & Assumptions
Given: Lebesgue measure on , the intervals , and the functions .
Uniform integrability means that for every there is such that for every . (A uniformly integrable family)
On finite measure spaces, uniform integrability is equivalent to -boundedness plus uniform absolute continuity. (On a finite measure space, uniform integrability is equivalent to L^1-boundedness plus uniform absolute continuity)
Verification
The series converges to a value below , so the intervals are pairwise disjoint subsets of . Also
If and , then ; if , then and Hence the family is uniformly integrable by [L1].
If were an integrable majorant for all , then almost everywhere on . Since the intervals are pairwise disjoint, contradicting integrability of .
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].
Sources
- Gerald B. Folland, Real Analysis, 2nd ed., Section 2.4, Example (iv)
- Terence Tao, 245A Notes 4: Modes of convergence, Example 7
- Gerald B. Folland, Real Analysis, 2nd ed., Section 2.4, Example (ii)
- Terence Tao, 245A Notes 4: Modes of convergence, Example 4
- Gerald B. Folland, Real Analysis, 2nd ed., Section 2.4, Example (iii)
- Richard F. Bass, Real Analysis for Graduate Students, Example 5.16