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Normed and Banach Spaces — Examples
1 · Prerequisites
- Absolute and Conditional Convergence; Rearrangement; Products
- Approximation and Compactness in C(K)
- 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
- Filters and Ultrafilters
- Finite Counting, Factorials and Binomial Coefficients
- Foundations of the Real Numbers for Analysis
- Function Space Topologies and the Exponential Law
- Ideals, Quotient Rings and the Isomorphism Theorems for Rings
- 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
- Normed and Banach Spaces
- 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
- Subspaces, Products, and Quotients
- Suprema and Infima
- 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 examples concrete: sequence spaces, bounded and continuous function spaces, a standard incomplete dense subspace, and the remetrisation warning that the topology of a vector space is weaker than its norm geometry. Each example depends only on the A-page completion and closed subspace results, plus earlier published theorems already in closure.
3 · Logical flowchart
4 · Definitions, theorems and proofs
None yet.
5 · Examples, counterexamples and false statements
is Banach for the supremum norm
Example
Let be the space of bounded scalar sequences with norm Then is a Banach space.
Facts & Assumptions
Given: A Cauchy sequence in for the supremum norm, with coordinates .
A Banach space is a normed space complete for its norm metric (Banach space).
Verification
For each fixed coordinate , the scalar sequence is Cauchy because . Let .
Since is Cauchy, choose with for . Fixing and letting coordinatewise gives for every , so is bounded and lies in .
Given , choose with for . Letting coordinatewise yields for every , so for .
Thus every supremum-norm Cauchy sequence in converges in , so is Banach by [L1].
is Banach for the supremum norm
Example
Let With the supremum norm inherited from , the space is Banach.
Facts & Assumptions
Given: A sequence in that is a supremum-norm limit of a sequence in .
The space is Banach for the supremum norm ( is Banach for the supremum norm).
A closed subspace of a Banach space is Banach (A closed subspace of a Banach space is Banach).
Verification
Fix and choose with . Because , there is with for all .
For , . Hence , so .
Step 2.1 shows that is closed in . Since is Banach by [L1], [L2] makes Banach.
is Banach for the supremum norm
Example
Let be a nonempty topological space, and let be the space of bounded continuous scalar-valued functions on with norm Then is a Banach space.
Facts & Assumptions
Given: A nonempty topological space and a Cauchy sequence in for the supremum norm.
Uniform limits of continuous functions are continuous (A uniform limit of continuous functions is continuous, so is closed in under the uniform metric).
A Banach space is a normed space complete for its norm metric (Banach space).
Verification
For each , the scalar sequence is Cauchy because . Define .
Choose with for . Fixing and letting pointwise gives for every , so is bounded.
Given , choose with for . Letting pointwise yields for . Thus uniformly, and [L1] makes continuous.
So every supremum-norm Cauchy sequence in converges in , and [L2] shows that is Banach.
is Banach when is compact metric
Example
If is a nonempty compact metric space, then the space of continuous scalar functions on , with the supremum norm, is a Banach space.
Facts & Assumptions
Given: A nonempty compact metric space .
Every bounded continuous function space is Banach for the supremum norm ( is Banach for the supremum norm).
A continuous real-valued function on a nonempty compact metric space is bounded and attains its extrema (A continuous real-valued function on a nonempty compact metric space is bounded and attains a greatest and a least value).
Verification
If , [L2] makes bounded. Hence as sets and the supremum norms agree.
Since is nonempty and compact, [L1] makes Banach for the supremum norm. By step 1.1, this is exactly with the same norm.
The finitely supported sequences form an incomplete normed space with different standard completions
Example
Let Then is an incomplete normed space for the supremum norm, its completion for that norm is , and for each its completion for the norm is .
Facts & Assumptions
Given: The finitely supported sequence space and, for a sequence , its truncations .
The space is Banach for the supremum norm ( is Banach for the supremum norm).
Any two completions of a normed space are uniquely linearly isometric (Any two completions of a normed space are uniquely linearly isometric).
The classical and hence spaces are Banach (The classical spaces are Banach spaces).
Verification
If , then and . So is dense in for the supremum norm.
For and , the truncations satisfy , so is dense in for the norm.
The sequence lies in but not in , while its truncations converge to in the supremum norm by step 1.1. Hence is not complete for that norm, and since is Banach by [L1], [L2] identifies the supremum-norm completion of with .
Because is Banach by [L3], the uniqueness statement [L2] identifies the -completion of with .
Polynomials are not complete in the supremum norm on a compact interval
Example
Let be real numbers, and let be the real polynomial functions on with the supremum norm. Then is not complete. Its completion is .
Facts & Assumptions
Given: Real numbers , the midpoint , and the function on .
The real Stone-Weierstrass theorem makes the polynomial algebra dense in for the supremum norm (Real Stone--Weierstrass theorem for compact metric spaces).
The space is Banach for the supremum norm ( is Banach when is compact metric).
Any two completions of a normed space are uniquely linearly isometric (Any two completions of a normed space are uniquely linearly isometric).
Verification
By [L1], the polynomial algebra is dense in , so in particular the continuous function lies in its supremum-norm closure.
The function is not a polynomial on : if a polynomial agreed with , then on it would satisfy , and on it would satisfy . So the polynomial would vanish on the interval , hence be identically zero, and similarly would be identically zero, forcing for all , impossible because .
Steps 1.1 and 1.2 show that is dense and proper in the Banach space , so it is not complete.
Since is Banach by [L2] and contains densely, [L3] identifies the completion of with .
Dictionary of the classical and Banach spaces
Example
The standard Banach-space dictionary is:
- is Banach for every ;
- is the counting-measure instance of ;
- is dense in for and dense in for the supremum norm.
Facts & Assumptions
Given: The classical spaces listed above.
The classical spaces are Banach (The classical spaces are Banach spaces).
The example of records its dense embeddings into and (The finitely supported sequences form an incomplete normed space with different standard completions).
Verification
The first two bullets are exactly the content of [L1].
The third bullet is exactly the content of [L2].
Combining steps 1.1 and 1.2 gives the stated dictionary.
An incomplete normed subspace need not be closed
Statement refuted
Every incomplete normed subspace of a normed space is closed.
Facts & Assumptions
Given: The supremum-norm inclusion .
The space is Banach ( is Banach for the supremum norm).
The space is incomplete and dense in for the supremum norm (The finitely supported sequences form an incomplete normed space with different standard completions).
A complete normed subspace is closed (A complete normed subspace is closed).
Counterexample
By [L2], the subspace is incomplete.
By [L2], the same subspace is dense in , so if it were closed then it would equal all of . But , since for example .
Therefore is an incomplete normed subspace that is not closed, refuting the statement. The ambient space is Banach by [L1], and [L3] explains why no contradiction occurs: [L3] goes in the opposite direction.
Topologically equivalent metrics on a vector space need not come from equivalent norms
Statement refuted
If two metrics on a vector space are topologically equivalent and one is induced by a norm, then the other is induced by an equivalent norm.
Facts & Assumptions
Given: A nonzero normed space and the norm metric .
The bounded remetrisation is a metric topologically equivalent to ( and are metrics uniformly equivalent to , so every metric space carries a bounded metric with the same topology, Topologically, uniformly and Lipschitz equivalent metrics on a set).
A norm metric satisfies for every scalar (A norm on a real vector space, the induced metric, and the dictionary with the metric axioms).
Counterexample
By [L1], the metric has the same topology as the original norm metric .
Suppose were induced by some norm on . Choose a nonzero vector ; then , so [L2] gives for every scalar .
The right-hand side of step 2.1 is unbounded as , but by definition for every . This contradiction shows that is not induced by any norm at all.
Hence is topologically equivalent to a norm metric while failing even to come from a norm, so it certainly does not come from a norm equivalent to the original one. This refutes the statement.
Sources
- Theo Buhler and Dietmar A. Salamon, Functional Analysis
- Andrew Lin and Casey Rodriguez, MIT 18.102 Introduction to Functional Analysis
- Gerald Teschl, Topics in Real and Functional Analysis
- Stone-Weierstrass Theorem (University of Chicago)
- Equivalence of metrics (Wikipedia)
- J. Demmel, MA221 Lecture 3: Vector Norms