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Finite Dimensional Normed Spaces and Riesz Lemma
1 · Prerequisites
- Binary Operations, Monoids, Groups and Subgroups
- Bounded Linear Operators and Quotient Spaces
- Compactness
- Compactness in Metric Spaces
- Completeness, Completion, and Uniform Continuity
- Complex Norms and Realification
- Complex Subspace Realification
- Complexification, Realification and Real Structures
- 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
- 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
- Linear Independence, Bases and Dimension
- Linear Transformations, Rank-Nullity and Quotient Spaces
- Metric Spaces
- 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
- 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
- Simple Field Extensions and the Construction of the Complex Numbers
- Subspaces, Products, and Quotients
- Suprema and Infima
- 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
This page packages the first finite-dimensional rigidity results for normed spaces: coordinate-space models, norm equivalence, completeness, closedness of finite-dimensional subspaces, and boundedness of linear maps from finite dimension. It then turns to Riesz's lemma and the compactness consequences that separate finite from infinite dimension, keeping the closed-unit-ball direction choice free and isolating the sharper Baire-cost remark for the countable-Hamel basis theorem. The page closes with the based Kuratowski embedding and the Wojdyslawski convex-hull closedness refinement.
3 · Logical flowchart
4 · Definitions, theorems and proofs
A chosen algebraic basis identifies a finite-dimensional normed space with a coordinate space
Statement
Let be a normed space over , read in the real case by A norm on a real vector space, the induced metric, and the dictionary with the metric axioms and the complex case by Complex norm and complex normed space. Let be an ordered basis (Basis of a vector space: a linearly independent spanning subset; and ordered basis: an injective finite list whose image is a basis), and write . Give its coordinate norm
Define
Then is a topological isomorphism of normed spaces in the sense of A topological isomorphism of normed spaces.
Facts & Assumptions
Given: A normed space over and an ordered basis .
An ordered basis is a finite list whose image is a basis (Basis of a vector space: a linearly independent spanning subset; and ordered basis: an injective finite list whose image is a basis), and A finite list is an ordered basis if and only if every equals for exactly one ; those scalars are the coordinates of in that ordered basis identifies its span with exactly the vectors of the form , with those coordinates unique.
A topological isomorphism of normed spaces is a bounded linear bijection whose inverse is bounded (A topological isomorphism of normed spaces).
For , every norm on is equivalent to the Euclidean norm, and any two norms on are equivalent (For all norms on are equivalent).
The map , , is a bijection with the stated coordinate arithmetic ( is the real coordinate plane, with coordinate arithmetic).
Complex norms have full complex absolute homogeneity (Complex norm and complex normed space). Their realifications carry the same norm and metric (Realification of a complex vector space by restriction of scalars, Complex modulus restricts to real absolute value, Realification preserves a complex norm and its metric). The coordinate function is a complex norm, including (The complex coordinate sum norm, including the zero space).
Real absolute value is definite, multiplicative and subadditive (Basic properties of the absolute value, The triangle inequality).
Finite real sums distribute over addition and scaling and preserve inequalities (Finite sums and finite products, by recursion, Laws of finite sums and finite products).
Proof
By [L1], every has exactly one coordinate list with . Therefore the displayed map is well defined, surjective, and injective.
is linear, because finite sums and scalar multiplication distribute over the coordinate formula: .
In the complex case, [L5] makes both and real norms on : for , separation uses injectivity in step 1.1, and homogeneity and the triangle inequality use step 1.2 and the norm on . The coordinate map is a real-linear bijection by [L4], so and are real norms on . If , the pairwise equivalence clause of [L3] gives a positive real such that for every . Thus . If , both spaces consist only of zero by [L1], and the inverse is bounded with bound zero.
Put , a finite real. Then so is bounded.
In the real case , the coordinate is a real norm: absolute-value definiteness, multiplicativity, and the triangle inequality give the three axioms by finite summation, including the empty list. The pullback is a norm on : definiteness uses step 1.1, and the triangle and homogeneity axioms come from the norm axioms on and the linearity of . If , then and the inverse of is the zero map, hence bounded. If , [L3] gives with for every , so for every . Thus is bounded in the real case.
Steps 1.1, 1.2, 2.1, 2.2, and 2.3 verify the three clauses of [L2]. Therefore is a topological isomorphism of normed spaces.
Remarks
- The proof uses the coordinate norm because it makes the boundedness of immediate. Any other standard coordinate norm would do, and on a fixed finite-dimensional coordinate space all of them are equivalent.
- The finite-dimensional language in the title is implemented here by the actual datum the page uses: a chosen ordered basis of finite length.
All norms on a finite-dimensional complex normed space are equivalent
Statement
Let be a complex vector space carrying two complex norms and , and suppose admits an ordered basis of finite length. Then and are equivalent in the sense of Equivalent complex norms.
Facts & Assumptions
Given: A complex vector space with two complex norms and , and an ordered basis .
For either norm on , the basis map from with the coordinate norm is a topological isomorphism (A chosen algebraic basis identifies a finite-dimensional normed space with a coordinate space).
Equivalent norms are exactly those satisfying for some positive real constants (Equivalent complex norms).
Proof
Let be the common algebraic basis map . Applied to the norm , [L1] gives constants such that for every .
Applied to the norm , [L1] gives constants such that for every .
Let and write , which is possible and unique by [L1]. Then Interchanging and gives
Taking and , step 2.1 is exactly the two-sided estimate of [L2], so the two norms are equivalent.
Remarks
- The proof does not need a separate norm-comparison theorem on : one coordinate isomorphism for each norm already supplies the comparison.
- The published theorem For all norms on are equivalent remains the real base case on which A chosen algebraic basis identifies a finite-dimensional normed space with a coordinate space rests.
Every finite-dimensional normed space is Banach
Statement
Let be a normed space over and assume admits an ordered basis of finite length. Then is a Banach space in the sense of Banach space.
Facts & Assumptions
Given: A normed space over with an ordered basis .
The basis map is a topological isomorphism (A chosen algebraic basis identifies a finite-dimensional normed space with a coordinate space).
is the real coordinate plane with coordinate arithmetic ( is the real coordinate plane, with coordinate arithmetic). The coordinate function is a complex norm (The complex coordinate sum norm, including the zero space), and realification preserves its metric (Realification preserves a complex norm and its metric).
A Banach space is a normed space complete for its norm metric (Banach space).
Proof
By [L1], it is enough to prove that is complete for the coordinate norm, because a bounded bijection with bounded inverse preserves Cauchy sequences and their limits.
In the real case , if then is complete trivially. If , [L2] applies directly to the norm on , so is complete.
In the complex case, if the coordinate space is a singleton and complete. If , let send each coordinate to its real and imaginary parts. By [L3] it is a real-linear bijection, and is a real norm on . It is complete by [L2]. Since , the bijection transports Cauchy sequences and limits exactly; thus is complete in its complex coordinate norm metric.
Let be a Cauchy sequence in , and write . Since is bounded, is Cauchy in ; by steps 1.2 and 1.3 it converges to some . Since is bounded, in . Thus every Cauchy sequence in converges in .
By [L4], step 2.1 says exactly that is Banach.
Remarks
- The only substantive input is completeness of finite-dimensional real coordinate space. Everything else is transport of structure.
A finite-dimensional normed subspace is closed
Statement
Let be a normed space over and let be a normed subspace over that same field: use Normed subspace for and A complex normed linear subspace for . If admits an ordered basis of finite length, including length zero, then is closed in . This holds in ZF, without a choice axiom; the ambient space need not be complete.
Facts & Assumptions
Given: A normed space over , a normed subspace , and an ordered basis of .
Such a normed space is Banach (Every finite-dimensional normed space is Banach).
An ordered basis is an independent finite list spanning its space; the empty list spans exactly the zero subspace (Basis of a vector space: a linearly independent spanning subset; and ordered basis: an injective finite list whose image is a basis).
The restricted norm on a normed subspace is the ambient one (Normed subspace, A complex normed linear subspace).
Fix an enumeration and a bijection ( is countably infinite, ). Rational numbers, identified with their real images, approximate every real number (Both and are dense in , and every nonempty open subset of is uncountable, clause 1).
A supplied total self-map and a starting value determine a sequence by recursion (The recursion theorem); every nonempty subset of has a least element (The well-ordering principle).
For every some integer satisfies (For every in a complete ordered field there is a natural with ).
Realification preserves the norm and metric (Realification of a complex vector space by restriction of scalars, Realification preserves a complex norm and its metric). A complex normed subspace realifies to a real normed subspace, and its supplied complex basis yields the real basis (A complex normed subspace and its finite basis realify). Complex coordinate arithmetic is given by is the real coordinate plane, with coordinate arithmetic.
Proof
If , then by [L2]. Every has the open ball of radius disjoint from , so its complement is open and is closed. It remains to treat .
For , in the real case put and . In the complex case put , , and , and use real scalars. Splitting complex coefficients proves real spanning; grouping a real relation into a complex relation among the proves independence. Thus is a supplied ordered real basis of , and its norm is still the restricted ambient norm. By [L1], is complete for this metric.
Define maps for as follows: is the empty tuple, and The unique inverse pair of each natural makes this a total definition. Finite recursion, or [L5] on states consisting of a stage and such a map, produces the maps uniformly; after stage keep the state fixed. By induction each is surjective: given a tuple of length , its initial tuple has a preimage under , its final coordinate has a preimage under , and maps to the entire tuple. This uses two witnesses for one tuple, not a family of selected enumerations. Define Its image is exactly the rational span of this finite basis.
This image is dense in . For and , let be the least index satisfying Existence follows from rational density and [L5] gives the least index. Surjectivity of gives a value of equal to , and Hence every ball in meets .
Let be an ambient adherent point of , meaning every ball about meets . For each , first such adherence and then step 3.1 give a point within of and a value within of . Thus the set is nonempty. Set and . This defines the sequence outright by a unique-index rule. By [L6] the error tends to zero, so in , and makes it Cauchy in the restricted metric of .
Completeness from step 1.2 supplies with in the restricted norm. Since the norm agrees with the ambient one, so . Every ambient adherent point therefore belongs to . A point outside consequently has a ball disjoint from , making the complement open and closed. Together with step 1.1 this proves all cases, without manufacturing a sequence in an arbitrary subset or using countable choice.
A linear map from a finite-dimensional normed space is bounded
Statement
Let and be normed spaces over the same scalar field, and assume admits an ordered basis of finite length. Then every linear map is a bounded linear operator in the sense of A bounded linear operator between normed spaces.
Facts & Assumptions
Given: Normed spaces and , a linear map , and an ordered basis .
The basis map is a topological isomorphism (A chosen algebraic basis identifies a finite-dimensional normed space with a coordinate space).
A bounded linear operator is a linear map satisfying one global norm bound (A bounded linear operator between normed spaces).
Linearity means (Linear map between vector spaces over the same field).
Proof
Let be the basis map from [L1]. Since is bounded, there is such that
Put , a finite real. If , then by [L3] so
Combining steps 1.1 and 1.2 gives Therefore is bounded, and with [L3] this makes a bounded linear operator by [L2].
Riesz lemma
Statement
Let be a normed space, let be a proper closed normed subspace (Normed subspace), and let . Then there exists such that and
Facts & Assumptions
Given: A normed space , a proper closed normed subspace , and a real with .
The subspace is proper and closed in .
Proof
By [A1], choose and put . Because is closed, its complement is open, so there is with . Hence for every , which gives .
Since , one has . By definition of the infimum, choose with Put Then .
Let . Because , the definition of gives Therefore the last inequality by step 2.1. Since was arbitrary, .
Step 3.1 produces a unit vector whose distance from exceeds , as required.
Remarks
- The proof uses only an approximate minimizer. No nearest-point theorem is assumed.
A normed space is locally compact if and only if it is finite-dimensional
Statement
Let be a normed space over , equipped with its norm topology. Then the following are equivalent.
- is locally compact (Locally compact topological space: every point has a compact neighbourhood; and what this says in a metric space).
- admits an ordered basis of finite length.
This is the page's precise reading of "finite-dimensional".
Facts & Assumptions
Given: A normed space over .
A chosen ordered basis yields a topological isomorphism with a coordinate space (A chosen algebraic basis identifies a finite-dimensional normed space with a coordinate space).
Riesz's lemma: for every proper closed normed subspace and there is a unit vector at distance from (Riesz lemma).
Compact metric spaces are totally bounded (A compact metric space is complete and totally bounded, and neither implication uses any choice principle).
is locally compact for ( is locally compact and -compact).
is the real coordinate plane ( is the real coordinate plane, with coordinate arithmetic).
In a metric space, local compactness at a point is equivalent to the existence of an open ball around that point contained in a compact subset (Locally compact topological space: every point has a compact neighbourhood; and what this says in a metric space).
Proof
Assume admits an ordered basis of length . If , the coordinate space is locally compact by [L4] when , and is compact, hence locally compact. If , then identifies with by [L5], so the same conclusion holds there. By [L1], is homeomorphic to that coordinate space, hence locally compact.
Assume now that is locally compact. By [L6], applied to the norm metric, has a compact neighbourhood containing some open ball with . The closed ball is a closed subset of and is therefore compact.
For the successor step, let . The finite list generates , so by deleting dependent terms if necessary one gets an ordered basis of finite length for . Thus by the contradiction hypothesis, and A finite-dimensional normed subspace is closed makes closed. Applying [L2] with yields a unit vector with . In particular for every . [L2, A finite-dimensional normed subspace is closed, choose]
Suppose for contradiction that admits no ordered basis of finite length. We recursively build, for each , unit vectors such that For choose any nonzero and normalize it.
Every lies in the closed ball after rescaling by : namely satisfies , so lies in that compact set. Also
By [L3], the compact metric space is totally bounded. Taking , it admits a finite -net. But one -ball can contain at most one of the points , since distinct ones are more than apart. Therefore a finite -net cannot cover arbitrarily large finite sets , contradiction.
The contradiction in step 4.1 shows that must admit an ordered basis of finite length. Together with step 1.1, this proves the equivalence.
Remarks
- The reverse implication uses only one finite recursion at a time. No choice principle is needed.
Under dependent choice, Riesz lemma builds an infinite separated sequence in the unit sphere
Statement
Assume the Axiom of Dependent Choice (The axiom of dependent choice: a relation in which every element is related to something admits an -indexed chain). Let be a normed space that is not spanned by any finite list, and let . Then there exists a sequence of unit vectors in such that
Facts & Assumptions
Given: Dependent Choice, a normed space that is not the span of any finite list, and a real with .
Dependent Choice produces an -indexed chain for an entire relation on a nonempty set (The axiom of dependent choice: a relation in which every element is related to something admits an -indexed chain).
If a subspace admits an ordered basis of finite length, then it is closed (A finite-dimensional normed subspace is closed).
Riesz's lemma gives a unit vector at distance from every proper closed subspace (Riesz lemma).
The span of a subset is the set of its finite linear combinations (Linear combination of a finite list, and the span as the smallest linear subspace containing ).
Proof
Let be the set of all finite lists of unit vectors in such that for all . The set is nonempty because any single unit vector lies in it: choose any nonzero and normalize it.
Define a relation on by when is obtained from by appending one more unit vector with . If , then the finite span is generated by a finite list, so by deleting dependent terms one obtains an ordered basis of finite length for . Since is not the span of any finite list, ; by [L2] it is closed. Now [L3] applies to and produces a unit vector with , so has an -successor. Thus is entire on .
By [L1], there is a sequence in with for every . Because each successor appends exactly one new term, the first entries stabilize: if denotes the last entry appended when passing from to , then every earlier remains in all later lists.
For , the vector was chosen with , and lies in that span. Hence . Every is a unit vector by the definition of . Therefore is the required separated sequence.
Remarks
- This lemma is the optional DC witness from the design. The compactness results on the page do not need it.
The closed unit ball is compact if and only if the normed space is finite-dimensional
Statement
Let be a normed space over and write
Then the following are equivalent.
- is compact in the norm metric (Open cover, subcover, compact metric space, and compact subset of a metric space).
- admits an ordered basis of finite length.
Facts & Assumptions
Given: A normed space over and its closed unit ball .
A chosen ordered basis yields a topological isomorphism with a coordinate space (A chosen algebraic basis identifies a finite-dimensional normed space with a coordinate space).
Riesz's lemma gives a unit vector at distance from every proper closed subspace (Riesz lemma).
Finite-dimensional normed subspaces are closed (A finite-dimensional normed subspace is closed).
Compact metric spaces are totally bounded (A compact metric space is complete and totally bounded, and neither implication uses any choice principle).
Closed and bounded subsets of are compact for (Heine-Borel in : with the Euclidean metric a subset of is compact if and only if it is closed and bounded, and the proof by bisection uses no choice principle; the same holds on the real line).
is the real coordinate plane ( is the real coordinate plane, with coordinate arithmetic).
Proof
Assume admits an ordered basis of length , and let be the coordinate isomorphism from [L1]. Then is closed in , because is continuous, and bounded in the coordinate norm, because is bounded.
Assume conversely that is compact. Then [L4] makes it totally bounded. Suppose for contradiction that admits no ordered basis of finite length.
Let be a finite -net, and put . The finite set generates , so by deleting dependent terms one gets an ordered basis of finite length for ; thus [L3] makes closed. Since is not finitely generated, .
In the real case , if then is compact. If , step 1.1 and [L5] show that is compact in , hence is compact as its homeomorphic image.
In the complex case , [L6] identifies with . Under that identification the coordinate norm is equivalent to a real norm on , so the bounded closed set is also closed and bounded in Euclidean space. If it is a singleton; if , [L5] makes it compact in , hence compact in and therefore in .
Applying [L2] with gives a unit vector with . Since is a -net in the unit ball and , some satisfies . But , which contradicts .
Therefore must admit an ordered basis of finite length. Together with steps 2.1 and 2.2, this proves the equivalence.
Remarks
- The reverse implication is choice free: compactness gives one finite net, and one application of Riesz's lemma is enough.
In an infinite-dimensional normed space the closed unit ball is not compact
Statement
Let be a normed space that admits no ordered basis of finite length. Then its closed unit ball
is not compact.
Facts & Assumptions
Given: A normed space with no ordered basis of finite length.
The closed unit ball is compact if and only if the space admits an ordered basis of finite length (The closed unit ball is compact if and only if the normed space is finite-dimensional).
Proof
If were compact, [L1] would force to admit an ordered basis of finite length.
That contradicts the hypothesis, so is not compact.
On an infinite-dimensional normed space, the identity operator is not compact
Statement
Let be a normed space that admits no ordered basis of finite length, and let be the identity map. Then is bounded, but it does not carry the closed unit ball of to a compact subset of . In that standard sense, the identity operator is not compact.
Facts & Assumptions
Given: A normed space with no ordered basis of finite length, its closed unit ball , and the identity map .
A bounded linear operator is a linear map satisfying one global norm bound (A bounded linear operator between normed spaces).
In this setting the closed unit ball is not compact (In an infinite-dimensional normed space the closed unit ball is not compact).
Proof
The identity map is linear and satisfies for every , so [L1] makes it a bounded linear operator.
One has . By [L2], that set is not compact. Therefore the identity operator does not send the closed unit ball to a compact subset of .
Remarks
- This item uses only the unit-ball criterion. It does not depend on a separate compact-operator definition item.
A Banach space has no countably infinite Hamel basis
Statement
Let be a Banach space over . Then has no countably infinite Hamel basis. Equivalently, there is no sequence of pairwise distinct vectors whose image is a basis of in the sense of Basis of a vector space: a linearly independent spanning subset; and ordered basis: an injective finite list whose image is a basis.
This holds in ZF, without any choice axiom. Here countably infinite means equinumerous with (Finite, countably infinite, countable, uncountable).
Facts & Assumptions
Given: A Banach space and, for contradiction, a sequence of pairwise distinct vectors whose image is a Hamel basis of .
A Banach space is complete for its norm metric (Banach space).
A normed space supplied with an ordered basis of finite length is complete (Every finite-dimensional normed space is Banach). We prove the needed closedness locally, rather than manufacture a sequence in an arbitrary subspace.
There is an enumeration ( is countably infinite), and rational numbers, identified with their real images, approximate every real number (Both and are dense in , and every nonempty open subset of is uncountable, clause 1).
Every nonempty subset of has a least element (The well-ordering principle). A supplied total function and starting point determine a sequence by recursion (The recursion theorem); stage-dependent rules are encoded on states containing the stage.
For every there is an integer with (For every in a complete ordered field there is a natural with ); also (For the sequence is null, and for the sequence diverges to , clause 1).
A complex Banach space retains its complete norm metric on restriction to real scalars (Realification preserves a complex norm and its metric, Banach space). Every complex scalar uniquely has the form with ( is the real coordinate plane, with coordinate arithmetic).
Proof
Fix and from [L3, L4]. Encode a finite word of naturals by , where and . To decode any natural, invert its outer pair to obtain , and invert the inner pair times, recovering the symbols in reverse order. If the final residue is not zero, return the empty word; otherwise return the recovered word. These are uniform finite recursions: one may retain the remaining length, current residue and recovered finite list as the state and stop changing the state when the remaining length is zero. Thus [L5] defines the decoder, and decoding an encoded word returns that word by induction and injectivity of . We have a total surjection from onto all finite words, without choosing separate enumerations for each length.
In the real case let . In the complex case let and , and regard as a real normed space. In either case is a real Hamel basis: in the complex case a finite real relation groups into a complex relation among the , forcing both real coefficients for each to vanish, and spanning follows by splitting each complex coefficient into real and imaginary parts. Completeness is unchanged.
Interpret a decoded symbol as the term , and interpret a decoded word as the sum of its terms, the empty word giving zero. Step 1.1 now defines a total function whose image is exactly the finite rational span of . In particular . For each fixed , the same decoder, with symbols having contributing zero, defines , where ; its image is exactly the rational span of this finite list.
For any finite expression and , if then . Otherwise put and let be the least natural with . Such an index exists by [L3]; [L5] determines it. The triangle inequality gives Consequently is dense in , and using only indices at most shows that is dense in . Only the displayed finite representation of the fixed vector is used, not a selection of representations for a family of vectors.
Each is proper since by real independence. Also , because every vector has a finite expression in the and a finite list of natural indices has an upper bound.
Fix and a point in the ambient closure of , meaning every ball around meets . For each , some satisfies , and density from step 3.1 gives some with . Hence the set of with is nonempty. Define to be its least member and . This defines one sequence outright by [L5]; no countable choice is used. The reciprocal estimate [L6] and the triangle inequality give in and show is Cauchy in .
The displayed list is an ordered real basis of by step 1.2, so [L2] supplies a limit of this already constructed Cauchy sequence. Then , whence . Therefore is closed: if a point outside it had no disjoint ball, it would belong to its closure, contrary to what we just proved. This argument uses completeness only on the specific sequence from step 4.1.
Every proper real linear subspace has empty interior. Indeed, if it contains then belongs to it, and subtraction gives inside it. For any nonzero , the vector belongs to that ball, and real scalar multiplication then puts in the subspace too; zero already belongs to it. Thus the subspace would be . In particular each is closed with empty interior.
Write and , and put . Balls are open by the triangle inequality. By step 6.1, is nonempty and open. Let be the least index with . Openness gives a radius about this point inside that set; [L6] gives an integer with . Therefore there is a least positive integer with .
Let be the set of triples with and . For any such triple the set is nonempty and open. Let be the least index with , and the least positive integer with and . Density, openness and [L6] prove these sets of indices nonempty. The resulting triple belongs to , so these formulas define a total function . Apply [L5] with initial state to obtain states for every . Put and . Then Thus . Every recurring selection was the minimum of a specified subset of .
For , nesting gives , so is Cauchy. By [L1] it converges to some . For fixed and all , Letting gives . Therefore for every . We used only the already constructed centers, not a choice of points from arbitrary closed sets.
Step 9.1 contradicts from step 3.2. Therefore the supposed countably infinite Hamel basis cannot exist. All sequences used above were defined by uniform coding, least indices, or recursion on a supplied function, so the proof requires no choice axiom.
Remarks
- The proof is written over the underlying real normed space in the complex case, so no separate complex Baire argument is needed.
Why the unrestricted complete-metric Baire theorem would overstate the choice cost here
Remark
The proof of A Banach space has no countably infinite Hamel basis does not need the full statement "every complete metric space is Baire". Its nested-ball argument uses a fixed dense sequence. The two available general results separating this route from the unrestricted principle are Separable complete metric spaces are Baire in ZF ↗ and Dependent Choice is equivalent to the complete-metric Baire principle over ZF ↗: over ZF, the separable theorem is choice free, whereas the unrestricted complete-metric theorem is equivalent to Dependent Choice.
That matters here because the countable Hamel basis already supplies an explicit countable dense set, namely the rational span of the basis. Using the sharper argument records the actual cost of the theorem proved on this page. Invoking the unrestricted theorem would still yield a correct proof of the Banach-space claim, but it would advertise a stronger choice principle than the written argument spends.
The based Kuratowski distance map into bounded continuous functions
Definition
Let be a nonempty metric space (Metric space: iff , symmetry, and the triangle inequality; pseudometric and ultrametric) and fix a basepoint . Inside the real function space of The vector space of all functions with pointwise operations, and as the case , write for the set of bounded continuous real-valued functions on , equipped with the supremum norm
For each , define a function by
The triangle inequality gives
so is bounded. The same inequality in the variable shows that is -Lipschitz, hence continuous. Therefore for every .
The resulting map
is the based Kuratowski distance map.
Remarks
- The subtraction by is what keeps the target bounded when the metric space itself is unbounded.
The based Kuratowski distance map is an isometric embedding
Statement
Let be a nonempty metric space, fix , and let be the based Kuratowski distance map of The based Kuratowski distance map into bounded continuous functions. Then is an isometric embedding in the sense of Isometry, isometric embedding, and the subspace metric on a subset:
Facts & Assumptions
Given: A nonempty metric space , a basepoint , and the map .
For each , defines a bounded continuous function on (The based Kuratowski distance map into bounded continuous functions).
An isometric embedding preserves all distances (Isometry, isometric embedding, and the subspace metric on a subset).
Proof
By [L1], the map is well defined as a map into . For any , the triangle inequality gives so Taking the supremum over yields .
Evaluating at gives and evaluating at gives the same value. Therefore the supremum norm is at least .
Steps 1.1 and 2.1 give for all , which is exactly [L2]. Hence is an isometric embedding.
Remarks
- The proof is two lines long once the target is chosen correctly. The real work is the based definition, which keeps the functions bounded on unbounded metric spaces.
Kuratowski-Wojdyslawski embedding theorem
Statement
Let be a bounded nonempty metric space. Then there is a Banach space and an isometric embedding such that is closed in its algebraic convex hull.
Concretely, one may take with the supremum norm and for any basepoint .
Consequently, every metrizable space embeds homeomorphically as a closed subset of a convex subset of a Banach space.
Facts & Assumptions
Given: A bounded nonempty metric space , a basepoint , and the based Kuratowski map .
is an isometric embedding (The based Kuratowski distance map is an isometric embedding).
Uniform limits of continuous functions are continuous (A uniform limit of continuous functions is continuous, so is closed in under the uniform metric).
The metric is bounded and 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 metrizable space is one whose topology is induced by some metric (Metrizable space: a topological space whose topology is induced by some metric; metrizability is topological, the metric is not).
Proof
The target is Banach for the supremum norm. Indeed, let be a Cauchy sequence in the supremum norm. Then each scalar sequence is Cauchy, so define . Fix with for ; letting gives for all , so is bounded. Given , fix with for ; letting yields for , so uniformly. By [L2], is continuous. Hence every Cauchy sequence converges in .
By [L1], is an isometric embedding of into the Banach space .
Let be a point of the algebraic convex hull of , so each and . Put If , then every pair with satisfies , hence all support points coincide and lies in the image.
Assume , and let . Evaluating at gives For each , the triangle inequality yields . Multiplying by and summing over gives Therefore Since this holds for every , the distance from to is at least . So no such lies in the closure of .
Steps 3.1 and 4.1 show that every point of the algebraic convex hull that lies in the closure of is already in . Thus is closed in its algebraic convex hull.
For the final claim, let be metrizable. If , the unique map into any Banach space is a homeomorphic embedding, and its image is closed in its algebraic convex hull. Assume now that . By [L4], choose a metric inducing . By [L3], the bounded metric induces the same topology. Applying steps 1.1 to 5.1 to gives an isometric embedding into a Banach space whose image is closed in its algebraic convex hull. Because and are topologically equivalent, that same map is a homeomorphic embedding for the original topology .
Remarks
- The closedness conclusion is relative to the algebraic convex hull. The proof above shows exactly why it need not be a statement about the whole Banach space.
5 · Examples, counterexamples and false statements
None yet.
Sources
- Daniel Daners, Introduction to Functional Analysis
- Tomasz Kochanek, Functional analysis, Lecture 1
- Gerald Teschl, Topics in Real and Functional Analysis
- Paul Howard and Eleftherios Tachtsis, On infinite-dimensional Banach spaces and weak forms of the axiom of choice
- Andrew Lin and Casey Rodriguez, MIT 18.102 Introduction to Functional Analysis
- Alan Sokal, Mathematics 3103, Handout 7 (2012–2013), Theorem 7.3 and footnote 4, pp. 3–5
- Christopher Heil, A Basis Theory Primer
- James Dugundji, Topology