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Measurable Functions and Simple Approximation
1 · Prerequisites
- Areas of Elementary Plane Figures
- Binary Operations, Monoids, Groups and Subgroups
- Compactness
- Compactness in Metric Spaces
- Completeness, Completion, and Uniform Continuity
- Construction of the Natural Numbers
- Construction of the Real Numbers via Cauchy Sequences
- Construction of the Real Numbers via Dedekind Cuts
- Continuity, IVT, EVT, and Uniform Continuity
- Countability and Uncountability
- Filters and Ultrafilters
- Foundations of the Real Numbers for Analysis
- Lebesgue Measure on Euclidean Space
- Limits of Real Functions
- limsup, liminf, and Subsequential Limits
- Linear Independence, Bases and Dimension
- Linear Transformations, Rank-Nullity and Quotient Spaces
- Measures and Their Basic Properties
- Metric Spaces
- Monotone Functions, Discontinuities, and Continuity Sets
- Monotone Sequences, Bolzano-Weierstrass, and Cauchy Completeness
- Non Measurable Sets and the Cost of Choice
- Order, Zorn's Lemma, and the Axiom of Choice
- Outer Measure and the Caratheodory Extension Theorem
- Relations, Functions, and Quotients
- Rings, Subrings, Integral Domains and Fields
- Rⁿ as a Normed Space; Vector-Valued Functions
- Roots, Rational Powers, and Classical Inequalities
- Separation Axioms: the Hierarchy
- Sequences and Limits
- Series: Convergence and the Nonnegative Tests
- Sigma Algebras and Borel Sets
- Subspaces, Products, and Quotients
- Suprema and Infima
- The Cantor Set, Baire Category, and Measure Zero in ℝ
- The Riemann Integral in Rᵐ and Jordan Content
- The Riemann Integral: Definition and Integrability
- The Topology of Euclidean Space
- 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
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
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 or is always the Borel sigma-algebra, not the Lebesgue sigma-algebra.
That convention is load-bearing. A Lebesgue measurable function on means
not a map into . The distinction is
exactly what makes the later counterexample
g \circ f with merely Lebesgue measurable possible.
The Borel sigma-algebra on the extended real line
Definition
The extended real line is
with the total order extending the usual order on and satisfying for every real (The extended real line , 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 and is generated by the rays
In particular, and are Borel sets.
A measurable function between measurable spaces
Definition
Let and be measurable spaces (Measurable spaces and measurable sets). A function is measurable when
Equivalently, the family
is a sigma-algebra on containing .
An indicator function is measurable exactly when its set is measurable
Statement
Let be a measurable space and let . The indicator function
is measurable as a map if and only if .
Facts & Assumptions
Given: A measurable space , a subset , and the indicator function .
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
If , then the preimage of any Borel set under is one of , , , or , because takes only the values and . Each of those sets lies in , so is measurable by [L1].
If is measurable, then
and is a Borel subset of . Hence [L1] gives . [given, L1]
Steps 1.1 and 1.2 prove the equivalence.
Borel measurable and Lebesgue measurable functions on
Definition
Assume the Axiom of Countable Choice (The Axiom of Countable Choice ()), so Assuming countable choice, is a sigma-algebra containing every elementary set and is a complete measure extending elementary volume makes a sigma-algebra. Let with .
-
A function is Borel measurable when it is measurable as a map
in the sense of A measurable function between measurable spaces.
-
A function is Lebesgue measurable when it is measurable as a map
where is the Lebesgue sigma-algebra of Lebesgue measurable sets, the family , and the restricted set function .
When , these are the corresponding notions for real-valued functions.
The positive and negative parts of a function
Definition
Let with as in The extended real line , its order, and the arithmetic that is left undefined. Its positive part and negative part are
Pointwise, both functions take values in , and one has
At each point at least one of and is zero.
A simple function and its canonical representation
Definition
Let be a measurable space. A function is simple when it is measurable and its range is finite.
If the distinct values taken by are , define
Then the measurable sets are pairwise disjoint, their union is , and
This expression is the canonical representation of : the coefficients are the distinct values of , and the sets are its level sets.
The sigma-algebra generated by a function
Definition
Let be a function and assume the target carries a Borel sigma-algebra .
The sigma-algebra generated by is
Because preimages preserve complements and countable unions, this is a sigma-algebra on . It is the smallest sigma-algebra on that makes measurable.
The convention is used only for pointwise products of measurable functions
On this page the symbol for two -valued measurable functions is a pointwise definition, not a limit rule. At points where one factor is and the other is infinite, we set
This convention exists only so that decompositions such as and the measurable-product theorem stay pointwise total on the extended reals. It does not contradict Null times divergent has no rule: with gives product limit , and with gives divergence, because that counterexample concerns limits of ordinary real products, not the value of a pointwise formula.
A generating family on the codomain suffices to test measurability
Statement
Let and be measurable spaces, let generate , and let be a function. If
then is measurable as a map .
Facts & Assumptions
Given: Measurable spaces and , a function , and a generating family for .
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
Let
Preimages preserve complements and countable unions, so is a sigma-algebra on . [L1, algebra]
By hypothesis, every member of lies in . Since [given, step 1.1] is the sigma-algebra generated by , one has .
Therefore for every , and [step 2.1, L1] [L1] says exactly that is measurable.
Threshold characterisations of real-valued and extended-real-valued measurability
Statement
Let be a measurable space and let . The following are equivalent:
- is measurable;
- for every real ;
- for every real ;
- for every real ;
- for every real .
Moreover, in any one of conditions 2 through 5 it is enough to test only rational thresholds .
Facts & Assumptions
Given: A measurable space and a function .
The Borel sigma-algebra on is generated by the rays with . (The Borel sigma-algebra on the extended real line)
A generating family on the codomain suffices to test measurability. (A generating family on the codomain suffices to test measurability)
Between any two distinct real numbers there lies a rational number. (The rationals embed densely in the reals)
Proof
By [L1], the threshold set is the preimage [L1, L2] . Therefore [L2] gives the equivalence of condition 1 and condition 2.
Suppose the sets are measurable for every rational . For a [L3, algebra] real ,
So conditions 2 and 5 are equivalent, and conditions 3 and 4 are equivalent. [step 1.1, algebra]
For every real ,
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]
For every real ,
Indeed, implies , and if then [L3] gives a rational with unless , in which case any rational 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]
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.
Continuous functions on Euclidean spaces are Borel measurable
Statement
Assume the Axiom of Countable Choice. Let . Every continuous map is Borel measurable in the sense of Borel measurable and Lebesgue measurable functions on .
Facts & Assumptions
Given: The Axiom of Countable Choice, natural numbers , and a continuous function .
A continuous map has Borel preimages of Borel sets. (A continuous map has Borel preimages of Borel sets)
Proof
Let be Borel. By [L1], the preimage [L1] is a Borel subset of .
By the definition of Borel measurability on Euclidean spaces, step 1.1 says [step 1.1] exactly that is Borel measurable.
Every monotone real function is Borel measurable
Statement
Every monotone function in the sense of Nondecreasing, increasing (strictly increasing), nonincreasing, decreasing, monotone and strictly monotone real functions on a subset of , with the dictionary to monotone sequences is Borel measurable.
Facts & Assumptions
Given: A monotone function .
A real-valued function is measurable exactly when all of its threshold sets are measurable. (Threshold characterisations of real-valued and extended-real-valued measurability)
Proof
Suppose first that is increasing. For each real , the threshold set [given] is upward closed: if and , then , so . Therefore is one of the four Borel sets , , , or for some real .
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 is decreasing, then is increasing and hence measurable by the first half, and therefore is measurable as well.
A map into is measurable exactly when its coordinates are measurable
Statement
Let , let be a measurable space, and let . Then is measurable if and only if each coordinate function is measurable.
Facts & Assumptions
Given: A natural number , a measurable space , and a function .
Rational open boxes generate the Borel sigma-algebra on . (For n at least one, open sets, closed sets, compact sets, open balls, boxes, rational open boxes, and rational half-open boxes generate the Borel sigma-algebra on R^n)
A generating family on the codomain suffices to test measurability. (A generating family on the codomain suffices to test measurability)
Real-valued measurability is equivalent to threshold measurability. (Threshold characterisations of real-valued and extended-real-valued measurability)
Proof
Suppose is measurable. Fix and a real . Then
The displayed strip is open, hence Borel in , so the preimage is measurable. By [L3], each coordinate is measurable. [L3, given]
Conversely, suppose every coordinate is measurable. Let [L1, L3, algebra] be a rational open box. Then
and each factor on the right is measurable by [L3]. Therefore for every rational open box . [L1, L3, algebra]
By [L1] and [L2], step 1.2 implies that is measurable. Together with [step 1.1, step 1.2, L1, L2] step 1.1, this proves the equivalence.
Composition with a Borel measurable outer map preserves measurability
Statement
Let , , and be measurable spaces. If is measurable and is measurable, then is measurable.
In particular, if is measurable and is a Borel measurable function on its codomain, then is measurable.
Facts & Assumptions
Given: Measurable spaces , , , a measurable map , and a measurable map .
Measurability means that preimages of measurable sets are measurable. (A measurable function between measurable spaces)
Proof
Let . Since is measurable, [L1] gives [given, L1] .
Since is measurable, [L1] applied again gives
So is measurable. [step 1.1, L1] ∎
Arithmetic and lattice operations preserve measurability whenever they are defined
Statement
Let be a measurable space and let be measurable. Then:
- is measurable for every real scalar ;
- , , , , and are measurable;
- if is pointwise defined, then is measurable;
- with the convention of The convention is used only for pointwise products of measurable functions, the pointwise product is measurable.
Facts & Assumptions
Given: A measurable space and measurable functions .
Extended-real measurability is equivalent to measurability of the threshold sets . (Threshold characterisations of real-valued and extended-real-valued measurability)
The positive and negative parts are and . (The positive and negative parts of a function)
In this proof, the pointwise product uses the page convention .
Proof
Scalar multiples are measurable. If , then [given, L1] ; if , then ; and if , the function is constant. So [L1] gives measurability of , and in particular of .
The threshold identities
show via [L1] that and are measurable. By [L2], this proves measurability of and ; replacing by also gives . [step 1.1, L1, L2]
Assume is pointwise defined. For every real ,
The inclusion from right to left is immediate. For the converse, if then either , in which case any rational works, or is finite and one may choose a rational with . Thus [L1] gives measurability of . [step 2.1, L1]
Suppose first that are nonnegative and measurable. [step 3.1, L1, A1] If , then . If , then
Again the inclusion from right to left is immediate. For the converse, if , choose a rational with and ; this is possible because either is finite positive and the rationals are dense, or , in which case any sufficiently large positive rational works. Hence nonnegative products are measurable by [L1]. [step 3.1, L1, A1]
For general measurable and , step 2.1 gives measurable nonnegative [step 2.1, step 3.1, step 4.1, L2, A1] functions . By step 4.1 the four products are measurable. Put
At each point, at least one of and is zero, because at least one of and at least one of is zero. So the difference is pointwise defined without the forbidden form, and step 3.1 makes it measurable. By the usual sign decomposition, , with the convention [A1] at the points. [step 2.1, step 3.1, step 4.1, L2, A1]
Steps 1.1 through 5.1 prove all four claims.
Sequential suprema, infima, limsup, liminf, and pointwise limits of measurable functions are measurable
Statement
Let be a measurable space and let be measurable for every . Then the functions
are measurable. The set
is measurable. In particular, if pointwise, then is measurable.
Facts & Assumptions
Given: A measurable space and measurable functions for .
Threshold measurability characterizes extended-real measurability. (Threshold characterisations of real-valued and extended-real-valued measurability)
For each , the limsup and liminf of the sequence satisfy
and the pointwise limit exists exactly when the limsup and liminf are equal. (Limit superior and limit inferior of a real sequence as and in , A real sequence converges to iff , and diverges to iff both equal )
Proof
Let and . Then for every real [L1, given] ,
Since each threshold set on the right is measurable, [L1] gives measurability of and . [L1, given]
For each , the tail functions [step 1.1, L2] and are measurable by step 1.1. Applying step 1.1 again to the sequences and and then using [L2] yields measurability of and .
Let and . The equality set [step 2.1, L1, L2] is measurable because
If or , a rational strictly between them separates the two sides; if , every rational lies on the same side of both values. So [L2] makes the pointwise-convergence set measurable. [step 2.1, L1, L2]
If pointwise, then [L2] gives [step 2.1, step 3.1, L2] . Since step 2.1 has already proved that both limiting functions are measurable, is measurable.
Every nonnegative measurable function admits an explicit increasing sequence of simple approximations
Statement
Let be a measurable space and let be measurable. For define
Then each is a simple measurable function,
and for every . If is a set on which , then uniformly on .
Facts & Assumptions
Given: A measurable space , a measurable function , and the dyadic truncations displayed above.
Threshold measurability characterizes measurable -valued functions. (Threshold characterisations of real-valued and extended-real-valued measurability)
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
For fixed , each set [L1, L2] and is measurable by [L1]. Hence is a measurable real-valued function. Its values belong to the finite set , so [L2] makes a simple function.
Fix . If , then and also [given, algebra] . If , choose with . Then and . At the finer scale , the same point lies in one of the two adjacent dyadic cells over that coarse cell, so is either or . Thus .
The inequalities of step 1.2 hold for every , so [step 1.2] . If , then for all the second case of step 1.2 applies and gives , hence . If , then for every , so .
If on a set , then for every the second case of [step 1.2, step 2.1] step 1.2 applies to every and gives . Therefore
so uniformly on . [step 1.2, step 2.1] ∎
Every measurable function admits simple approximations dominated by its absolute value
Statement
Let be a measurable space and let be measurable. Then there is a sequence of simple functions such that
and for every .
Facts & Assumptions
Given: A measurable function .
The positive and negative parts satisfy , , and at each point at least one of is zero. (The positive and negative parts of a function)
The arithmetic-and-lattice theorem makes and measurable. (Arithmetic and lattice operations preserve measurability whenever they are defined)
Every nonnegative measurable function admits an increasing sequence of simple approximations. (Every nonnegative measurable function admits an explicit increasing sequence of simple approximations)
Proof
By [L2], the functions and are measurable and nonnegative. Applying [L1, L2, L3] [L3] to them gives simple functions and .
Put . Because and are simple, is a [step 1.1, L1] simple real-valued function. At each point, [L1] makes at least one of and equal to , so
Also pointwise because and . [step 1.1, L1] ∎
On a complete measure space, equality almost everywhere preserves measurability
Statement
Let be a complete measure space, let be measurable, and let satisfy almost everywhere. Then is measurable.
Facts & Assumptions
Given: A complete measure space , a measurable function , a function , and a measurable null set such that on .
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)
Threshold measurability characterizes measurable -valued functions. (Threshold characterisations of real-valued and extended-real-valued measurability)
Proof
Fix a real . On , the equality gives
Therefore
[given, algebra]
The set is measurable by [L2]. The set is a [step 1.1, L1, L2] subset of the measurable null set , so [L1] makes it measurable. Hence is measurable for every real .
By [L2], step 2.1 proves that is measurable.
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 be a measure space and let be its completion. If is measurable with respect to , then there is an -measurable function such that almost everywhere.
Facts & Assumptions
Given: The Axiom of Countable Choice, a measure space , its completion , and an -measurable function .
Every measurable function admits simple approximations dominated by its absolute value. (Every measurable function admits simple approximations dominated by its absolute value)
A completed measurable set has the form with and contained in a measurable null set. (The completion domain and proposed completed set function of a measure space)
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)
Pointwise limsup of a sequence of measurable functions is measurable. (Sequential suprema, infima, limsup, liminf, and pointwise limits of measurable functions are measurable)
Proof
By [L1], choose simple -measurable functions [L1, choose] with and for every . Write the canonical representation of as
where the are pairwise disjoint completed measurable level sets. [L1, choose]
For each pair , apply [L2] to and choose [L2, L3, choose] together with a completed null set such that with . Because , the sets remain pairwise disjoint. Define
Then each is -measurable and simple. Let . By [L3], is a completed measurable null set, and for every one has for all . [L2, L3, choose]
Define
By [L4], the function is -measurable. If , then step 1.2 gives for every , and step 1.1 gives , so . Hence on . [step 1.1, step 1.2, L4]
The null set is measurable in the completion by [L3], so step 2.1 says [step 2.1, L3] exactly that almost everywhere. Since is -measurable, it is the required base-measurable representative.
Doob-Dynkin factorization through the sigma-algebra generated by a function
Statement
Let and . Then is -measurable if and only if there is a Borel measurable function such that
Facts & Assumptions
Given: Functions and .
The sigma-algebra generated by is . (The sigma-algebra generated by a function)
Threshold measurability characterizes -valued measurability. (Threshold characterisations of real-valued and extended-real-valued measurability)
Proof
If for a Borel measurable , then for every Borel set [L1] ,
because is Borel in and [L1] describes exactly the sets whose preimages under lie in . So is -measurable. [L1]
Conversely, assume is -measurable. For each rational [step 1.1, L1, L2, algebra] , the threshold set lies in by [L2], so [L1] provides a Borel set with
Define
Then each is Borel, the family is increasing in , and
for every rational , because . [L1, L2, algebra]
For , define
with the infimum taken in , so the empty-set case gives . Because the sets are increasing,
so [L2] makes Borel measurable. [step 2.1, L2]
Fix and write . If is rational, then [step 2.1, step 3.1, L2] , so and therefore . If is rational, then , so and therefore . Thus is at once at least every rational below and at most every rational above , which forces .
Steps 1.1 and 4.1 prove the two directions of the equivalence.
5 · Examples, counterexamples and false statements
FALSE: if every level set of a real-valued function is measurable, then the function is measurable
Statement
False claim. If every level set 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 , and a Vitali set .
Assuming choice, Vitali sets exist. (Assuming choice on the cosets of in , a Vitali set in exists)
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
Define by [given, L1] for and for . Every level set of is empty, a singleton, or a two-point set, hence measurable.
The set is exactly , because on the [step 1.1, L2] values lie in and on they lie in . By [L2], the set is not measurable, so is not measurable.
FALSE: if the absolute value is measurable, then the function is measurable
Statement
False claim. If is measurable, then is measurable.
Facts & Assumptions
Given: The Axiom of Choice, the Lebesgue measurable-space structure on , and a Vitali set .
Assuming the Axiom of Choice, Vitali sets exist. (Assuming choice on the cosets of in , a Vitali set in exists)
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
Define by on and on [given, L1] . Then is the constant function , hence measurable.
But
which is not measurable by [L2]. So is not measurable even though is. [step 1.1, L2] ∎
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 , a Vitali set , and the family of indicator functions on .
Assuming choice, Vitali sets exist and are not Lebesgue measurable. (Assuming choice on the cosets of in , a Vitali set in exists, Assuming the Axiom of Choice, a Vitali set is not Lebesgue measurable)
The indicator of a measurable set is measurable. (An indicator function is measurable exactly when its set is measurable)
Refutation
Each singleton is measurable, so [L2] makes every [given, L2] measurable.
The pointwise supremum of the family is
Since is not measurable by [L1], the function is not measurable. So an uncountable supremum of measurable functions can fail to be measurable. [step 1.1, L1, L2] ∎
FALSE: equality almost everywhere with a measurable function implies measurability
Statement
False claim. If equals a measurable function almost everywhere, then is measurable. This fails on incomplete measure spaces.
Facts & Assumptions
Given: The Axiom of Choice and the Borel measure space , the Cantor set , and the homeomorphism from onto .
The set is compact and has Lebesgue measure , so it has positive outer measure; every positive-outer-measure subset of contains a nonmeasurable subset. (The homeomorphism sends the Cantor set onto a compact set of Lebesgue measure , Every subset of of positive Lebesgue outer measure contains a nonmeasurable subset)
The Cantor set has Lebesgue measure zero, and Lebesgue measure is complete. (The Cantor set is an uncountable subset of of Lebesgue measure zero, Assuming countable choice, is a sigma-algebra containing every elementary set and is a complete measure extending elementary volume)
The map is a homeomorphism from onto . (The map is a homeomorphism from onto )
Refutation
By [L1], choose a nonmeasurable subset , and put [L1, L2, L3, choose] . Since and is Lebesgue null, [L2] makes Lebesgue measurable. If were Borel, then continuity of from [L3] would make Borel in the subspace , hence Lebesgue measurable, which contradicts the choice of . So is Lebesgue measurable but not Borel.
Let and on . The function is Borel [step 1.1, L2] measurable, and on , so almost everywhere with respect to because is a measurable null set by [L2]. But
and is not Borel by step 1.1, so is not measurable on this incomplete measure space. [step 1.1, L2] ∎
FALSE: composing a Lebesgue measurable function with a continuous map preserves measurability
Statement
False claim. Let carry their trace Lebesgue sigma-algebras. If is continuous and is Lebesgue measurable, then is Lebesgue measurable.
Facts & Assumptions
Given: The Axiom of Choice, the Cantor set , the homeomorphism from onto , and .
The compact set has positive Lebesgue measure and therefore contains a nonmeasurable subset . The set is Lebesgue null, Lebesgue measure is complete, and is a homeomorphism. (The homeomorphism sends the Cantor set onto a compact set of Lebesgue measure , Every subset of of positive Lebesgue outer measure contains a nonmeasurable subset, The Cantor set is an uncountable subset of of Lebesgue measure zero, Assuming countable choice, is a sigma-algebra containing every elementary set and is a complete measure extending elementary volume, The map is a homeomorphism from onto )
The indicator of a measurable set is measurable. (An indicator function is measurable exactly when its set is measurable)
Refutation
Choose a nonmeasurable by [L1], put [L1, L2, choose] , let , and let . Completeness makes Lebesgue measurable in , hence measurable in the trace sigma-algebra on , so [L2] makes measurable, while [L1] makes continuous.
But
which does not lie in the trace sigma-algebra , even though is measurable and is continuous. [step 1.1, L1] ∎
FALSE: a pointwise limit of continuous functions is continuous almost everywhere
Statement
False claim. A pointwise limit of continuous functions on is continuous almost everywhere.
Facts & Assumptions
Given: The fat Cantor set .
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)
Every closed subset of a metric space is the zero set of a continuous real function. (In a metric space every closed set is a zero set and a , and the distance function separates a point from a closed set, so every metrizable space is Tychonoff and perfectly normal)
Refutation
By [L2], there is a continuous function with [L2, choose] . Put , and for define
Each is continuous, because it is built from by continuous algebraic operations and the denominator is everywhere positive. [L2, choose]
If , then and for every . If , [step 1.1, L1] then , so and . Thus the pointwise limit is . Since is closed and has empty interior by [L1], every point of is a boundary point of , and the indicator is discontinuous at every such point. Because is not Lebesgue null by [L1], the discontinuity set has positive measure.
Sources
- Sheldon Axler, Measure, Integration and Real Analysis, Section 2B
- John K. Hunter, Measure Theory, Chapter 3
- John K. Hunter, Measure Theory, Definition 3.1
- John K. Hunter, Measure Theory, Definition 3.3
- Sheldon Axler, Measure, Integration and Real Analysis, Section 2E
- Sheldon Axler, Measure, Integration and Real Analysis, Definition 2.88
- John K. Hunter, Measure Theory, Section 3.1
- Mathematics@CUHK, Martingale Theory I, Section 2.6
- John K. Hunter, Measure Theory, Proposition 3.2
- Sheldon Axler, Measure, Integration and Real Analysis, Proposition 2.52
- John K. Hunter, Measure Theory, Propositions 3.4 and 3.5
- John K. Hunter, Measure Theory, Section 3.2
- Sheldon Axler, Measure, Integration and Real Analysis, Proposition 2.53
- Sheldon Axler, Measure, Integration and Real Analysis, Theorem 2.89
- John K. Hunter, Measure Theory, Section 3.5
- Sheldon Axler, Measure, Integration and Real Analysis, Theorem 2.95
- Sheldon Axler, Measure, Integration and Real Analysis, Exercise 29
- John K. Hunter, Measure Theory, Example 2.22
- John K. Hunter, Measure Theory, Definition 3.3 and Example 2.22
- Smith-Volterra-Cantor set (Wikipedia)