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The Spaces Holder Minkowski and Riesz Fischer: Examples and Counterexamples
1 · Prerequisites
- Absolute and Conditional Convergence; Rearrangement; Products
- Binary Operations, Monoids, Groups and Subgroups
- 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
- 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
- Improper Integrals
- Limits of Real Functions
- limsup, liminf, and Subsequential Limits
- Linear Independence, Bases and Dimension
- Linear Transformations, Rank-Nullity and Quotient Spaces
- Measurable Functions and Simple Approximation
- Measures and Their Basic Properties
- Metric Spaces
- Modes of Convergence Egorov and Lusin
- Monotone Functions, Discontinuities, and Continuity Sets
- 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
- Power Series and Real-Analytic Functions
- Properties of the Integral and the Working FTC
- Relations, Functions, and Quotients
- Rings, Subrings, Integral Domains and Fields
- Rⁿ as a Normed Space; Vector-Valued Functions
- Roots, Rational Powers, and Classical Inequalities
- Sequences and Limits
- Sequences and Series of Functions; Uniform Convergence
- Series: Convergence and the Nonnegative Tests
- Sigma Algebras and Borel Sets
- Simple Field Extensions and the Construction of the Complex Numbers
- Suprema and Infima
- The Cantor Set, Baire Category, and Measure Zero in ℝ
- The Derivative and the Mean Value Theorems
- The Exponential Function
- The Lebesgue Integral and the Convergence Theorems
- The Logarithm and General Powers
- The Lᵖ Spaces Holder Minkowski and Riesz Fischer
- The Riemann Integral: Definition and Integrability
- The ZFC Axioms and the Basic Set Constructions
- Topological Spaces and Continuity
- Topology of ℝ
- Triangularisation, Generalised Eigenspaces and Jordan Canonical Form
- Vector Spaces, Linear Subspaces, Span and Direct Sums
2 · Summary
The companion page keeps the standard witnesses next to the main theorem chain: the power-function families for inclusion thresholds, the counting-measure dictionary, the essential-supremum and Holder-equality models, the explicit computation, and the exact failures the main page warns about.
3 · Logical flowchart
4 · Definitions, theorems and proofs
None yet.
5 · Examples, counterexamples and false statements
on and on calibrates membership
Example
Fix and let
on with Lebesgue measure. Then for every :
- exactly when .
- exactly when .
So the single power family produces both inclusion failures on .
Facts & Assumptions
Given: Real numbers and .
Membership in means finiteness of (The function space for ).
Positive-base power functions have the usual antiderivatives away from the logarithmic endpoint, and (Continuity and derivatives of positive-base real powers, The natural logarithm has derivative 1/x and equals the integral from 1 to x of 1/t).
The comparison tests for improper integrals are available (Comparison tests for improper integrals).
Verification
Proof technique: Integrate on and on using the real-power antiderivative and compare the two thresholds and .
Because and , [L1] reduces both claims to the improper integrals of .
On , the antiderivative is when , so the improper integral converges when , that is, when . If , it is , which diverges by [L2]. If , then on , so divergence follows from [L2] and the comparison test [L3].
On , the same antiderivative converges when , that is, when . If , it is again , which diverges by [L2]. If , then for , so divergence follows from [L2] and the comparison test [L3].
Steps 2.1 and 2.2 prove the two threshold claims.
membership in
Example
For , define a sequence on by and for . Then belongs to exactly when
Facts & Assumptions
Given: Real numbers and .
is the counting-measure version of ( is the space of counting measure).
The real -series converges exactly when (The p-series for a real exponent p converges exactly when p is greater than one).
Verification
Proof technique: Apply the real -series test to the series and read off the threshold .
By [L1], the sequence lies in exactly when [L1, given] converges.
By [L2], that series converges exactly when .
Finite counting measure on points recovers -norms
Example
Let , let with counting measure, and let be given by . Then
and
For every rational , these are exactly the published -norms on from The -norms for rational , and ; the displayed finite-sum formula itself remains valid for every real .
Facts & Assumptions
Given: An integer , the finite set , and a function .
is the counting-measure version of ( is the space of counting measure).
For rational , The -norms for rational , and defines the finite-dimensional -norms by the same finite-sum formula, and for it defines the same maximum norm.
Verification
Proof technique: Unwind the counting-measure integral on a finite set and compare it term by term with the published -norms on .
Extending by zeros outside turns it [L1, given] into a sequence in the setting of [L1]. The resulting and formulas are exactly the two displayed expressions.
In the ranges stated in [L2], those expressions are exactly the published [step 1.1, L2] norms on . For other real , step 1.1 still gives the displayed functional, without claiming that the earlier finite-dimensional page called it a norm. ∎
Indicator of the rationals has zero essential supremum but pointwise supremum one
Example
On with Lebesgue measure, let . Then
So essential supremum and pointwise supremum need not agree.
Facts & Assumptions
Given: The function on .
The essential supremum is the infimum of the essential bounds (The essential supremum of a measurable function with respect to a measure).
is countable, and every at most countable subset of is null ( is countably infinite, Every at most countable subset of has measure zero).
Verification
The pointwise supremum is because on every rational point of .
If , then , which is null by [L2]; if , then , which is also null. Hence every is an essential bound in the sense of [L1], and therefore .
Steps 1.1 and 1.2 prove the two claims.
Proportional functions realise the equality case of Holder
Example
Fix , let be its conjugate exponent, and work on with Lebesgue measure. For positive constants , define
Then
Facts & Assumptions
Given: Constants , an exponent , and its conjugate .
Equality in Holder holds when and are proportional almost everywhere (Equality in Holder's inequality for ).
Verification
Proof technique: Choose nonnegative functions with and proportional almost everywhere and invoke the equality theorem.
The functions satisfy [given] so almost everywhere.
Applying [L1] gives equality in Holder: [L1, step 1.1] ∎
A two-step function shows the norm converging to the essential supremum
Example
On with Lebesgue measure, let
Then
and therefore as .
Facts & Assumptions
Given: The two-step function above.
The norms of essentially bounded functions converge to the essential supremum ( norms converge to the essential supremum for essentially bounded functions).
Verification
Proof technique: Compute the -norms explicitly for a two-step simple function with two distinct values and let tend to infinity.
Direct computation gives [given, algebra]
Hence [L1, step 1.1, algebra] For , its bracket lies between and , so its power lies between and and therefore tends to . Thus . This agrees with [L1] because the essential supremum of is . ∎
The parallelogram law on two indicator functions in
Example
On with Lebesgue measure, let
Then
Facts & Assumptions
Given: The two indicator functions and above.
The parallelogram law has already been proved (The parallelogram law in ).
Verification
Proof technique: Evaluate all four norms on a pair of simple indicator functions and compare the two sides directly.
Since and are disjoint indicators of sets of measure , [given, algebra]
Therefore [L1, step 1.1] exactly as [L1] predicts. ∎
is not a subset of on the line
Statement refuted
On with Lebesgue measure, every function lies in .
Facts & Assumptions
Given: The power-family thresholds from on and on calibrates membership.
For , one has exactly when ( on and on calibrates membership).
Counterexample
Proof technique: Use the power-function family near with .
Choose and set . Then [L1, given] , so [L1] gives . But , so [L1] also gives .
Thus is an function on that does not lie in , [step 1.1] refuting the claim. ∎
is not a subset of on the line
Statement refuted
On with Lebesgue measure, every function lies in .
Facts & Assumptions
Given: The power-family thresholds from on and on calibrates membership.
For , one has exactly when ( on and on calibrates membership).
Counterexample
Proof technique: Use the power-function family at infinity with .
Choose and set . Then [L1] , so [L1] gives . But , so gives .
Thus is an function on that does not lie in , [step 1.1] refuting the claim. ∎
The published typewriter sequence shows why Riesz-Fischer only promises a subsequence
The published false statement FALSE: convergence in L^1(mu) forces almost-everywhere convergence records the typewriter sequence: it converges in but has no pointwise limit anywhere. So the subsequence clause in Riesz-Fischer completeness of for and -convergent sequences have almost-everywhere convergent subsequences is not cosmetic. Without it, the theorem would be false already on .
The half-norm fails the triangle inequality on two indicators
Statement refuted
On every measure space, the functional satisfies the triangle inequality.
Facts & Assumptions
Given: The non-norm proposition The -functional need not be a norm for .
The proof of The -functional need not be a norm for uses two disjoint equal-mass indicators to violate the triangle inequality.
Counterexample
Proof technique: Take two disjoint indicators of equal positive measure. Then the -functional of the sum exceeds the sum of the two -functionals.
On with Lebesgue measure, let [L1, given, algebra] and . Then while
Therefore [step 1.1, L1] so the triangle inequality fails. This is exactly the phenomenon summarized in [L1]. ∎
A nonzero function on a null set has zero seminorm
Statement refuted
Every nonzero measurable function has positive seminorm.
Facts & Assumptions
Given: The rational indicator on .
is countable and countable subsets of are null ( is countably infinite, Every at most countable subset of has measure zero).
Null functions are exactly the zero-seminorm class in every range treated on this page (Null functions form a linear subspace and are exactly the zero-seminorm class).
Counterexample
Proof technique: Use the indicator of a countable null subset of . It is not the zero function, but its -seminorm and essential supremum both vanish.
Let . Then is not the zero function, [given] because for every rational .
By [L1], the support of is null, so almost everywhere. Therefore [L1, L2] [L2] gives in every finite- range treated on the page, and also .
Thus a nonzero measurable function can have zero seminorm.
A Cauchy sequence in calligraphic can converge to two distinct functions
Statement refuted
In the representative space , the -distance always gives unique limits.
Facts & Assumptions
Given: A nonzero null-supported function from A nonzero function on a null set has zero seminorm.
The previous counterexample supplies a measurable function with (A nonzero function on a null set has zero seminorm).
is the representative function space before quotienting (The function space for ).
Counterexample
Proof technique: Take the constant sequence equal to a nonzero function supported on a null set. Its distance to the zero function is , so it converges to both itself and in the pseudometric on calligraphic .
Let for every , where is the function from [L1]. Then [L1, L2] is constant, hence Cauchy in the representative -distance.
Also [L1, step 1.1] for every . So the same sequence converges both to and to , even though those two functions are distinct pointwise.
Therefore the representative-space distance does not have unique limits [step 2.1] before passing to almost-everywhere classes. ∎
FALSE: includes into on every measure space when
Statement
For every measure space and every exponents , one has .
Facts & Assumptions
Given: The two power-function counterexamples on .
There is an function on that is not in ( is not a subset of on the line).
There is an function on that is not in ( is not a subset of on the line).
Refutation
Proof technique: Refute with the two power-function counterexamples on the line: one witness lies in and another lies in .
Taking and , [L1] already contradicts the claim.
The reverse failure [L2] shows why the line supports neither global [L2] inclusion.
Hence the displayed universal inclusion statement is false.
FALSE: the -seminorm on calligraphic is a norm
Statement
On the representative space , the functional is a norm.
Facts & Assumptions
Given: A nonzero function with zero seminorm.
The previous counterexample supplies a measurable function with (A nonzero function on a null set has zero seminorm).
A norm must satisfy the separation axiom (A norm on a real vector space, the induced metric, and the dictionary with the metric axioms).
Refutation
Proof technique: Refute with a nonzero function supported on a null set, whose seminorm is .
Let be the function from [L1]. Then pointwise but [L1] .
This violates the separation axiom in [L2], so the -seminorm on [step 1.1, L2] is not a norm. ∎
FALSE: the essential supremum equals the pointwise supremum
Statement
For every measurable function, the essential supremum equals the pointwise supremum.
Facts & Assumptions
Given: The rational-indicator example on .
The function has pointwise supremum but essential supremum (Indicator of the rationals has zero essential supremum but pointwise supremum one).
Refutation
Proof technique: Refute with the indicator of the rationals on , whose pointwise supremum is but whose essential supremum is .
The single function from [L1] already violates the claimed equality.
Therefore the statement is false.
FALSE: representatives of every -Cauchy sequence converge pointwise almost everywhere
Statement
For every Cauchy sequence in and every choice of measurable representatives , the sequence converges pointwise almost everywhere.
Facts & Assumptions
Given: The published typewriter-sequence false statement.
The published false statement FALSE: convergence in L^1(mu) forces almost-everywhere convergence supplies a sequence converging in but not almost everywhere.
Refutation
Proof technique: Refute in by the published typewriter witness: the sequence converges in norm and therefore is Cauchy, but it has no pointwise limit anywhere on .
The sequence from [L1] converges in , hence is Cauchy in .
The same source records representatives that fail to converge almost [L1, step 1.1] everywhere. So representatives of a Cauchy sequence in need not converge pointwise almost everywhere.
Therefore the universal claim is false.
FALSE: with its -functional is a normed space
Statement
The space with the functional is a normed space.
Facts & Assumptions
Given: The explicit half-norm triangle-inequality failure.
The previous counterexample exhibits functions with (The half-norm fails the triangle inequality on two indicators).
A normed space requires a norm, hence the triangle inequality (A norm on a real vector space, the induced metric, and the dictionary with the metric axioms).
Refutation
Proof technique: Refute with the explicit -triangle-inequality failure on two indicators.
The functions from [L1] violate the triangle inequality required by [L2].
Therefore with is not a normed space.
FALSE: Holder equality forces the functions themselves to be proportional
Statement
Whenever equality holds in Holder's inequality, the two functions themselves are proportional almost everywhere.
Facts & Assumptions
Given: The endpoint pair on with Lebesgue measure.
Holder's inequality includes the endpoint cases (Holder's inequality for integrals, including the endpoint cases).
The strict proportionality criterion on and was proved only for (Equality in Holder's inequality for ).
Refutation
Proof technique: Refute at the endpoint , with and on a proper positive-measure subset . Equality holds, but the functions are not proportional on the whole space.
Let , let , and let . Then [L1, given, algebra] So equality holds in Holder:
There is no constant with almost everywhere, because on [L2, step 1.1] one would need while on one would need . This does not contradict [L2], because [L2] does not cover the endpoint .
Thus equality in Holder does not force the functions themselves to be [step 1.1, step 2.1] proportional almost everywhere. ∎
Sources
- Richard L. Wheeden and Antoni Zygmund, Measure and Integral, Chapter 8
- John K. Hunter, Measure Theory, Chapter 17
- Richard L. Wheeden and Antoni Zygmund, Measure and Integral, Theorems 8.12 and 8.13
- John K. Hunter, Measure Theory, Definition 7.3
- Gerald B. Folland, Real Analysis, 2nd ed., Section 2.5
- Sheldon Axler, Measure, Integration & Real Analysis, Holder's Inequality
- Richard L. Wheeden and Antoni Zygmund, Measure and Integral, Theorem 8.1
- John K. Hunter, Measure Theory, Chapter 15
- Gerald B. Folland, Real Analysis, 2nd ed., Section 2.4, Example (iv)
- Terence Tao, 245A Notes 4: Modes of convergence, Example 7
- Richard L. Wheeden and Antoni Zygmund, Measure and Integral, Theorem 8.16
- Sheldon Axler, Measure, Integration & Real Analysis, Section 7B
- Richard L. Wheeden and Antoni Zygmund, Measure and Integral, Theorem 8.2
- John K. Hunter, Measure Theory, Section 7.2