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  • AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
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These labels describe origin, not correctness: citations and verification chips remain separate evidence.

Dual Spaces Adjoint Operators and Annihilators — Examples

1 · Prerequisites

2 · Summary

Coordinate functionals, shifts, point masses, and finite-dimensional matrices make the transpose explicit. The counterexamples separate dense range from surjectivity and show why the general annihilator formula uses weak-star closure. Complex Banach transposes use a bilinear pairing without conjugation.

3 · Logical flowchart

4 · Definitions, theorems and proofs

RemarkRemark: Literature-sourcedProof: Not applicablejudge pass (gpt-5.6-terra)audited 2026-09-07Open item page →

Two different Riesz representation theorems

Remark

For a locally compact Hausdorff space K, The bounded complex dual of C_0(X) is regular complex measures identifies the complex continuous dual of C0(K;C) with finite regular complex Borel measures, with functional norm equal to total variation. This is the Riesz–Markov–Kakutani representation. The Hilbert-space Riesz theorem is a different representation by inner-product vectors and belongs to the later Hilbert-space development. The evaluation pairing from The dual space X^* of a normed space and its dual norm is not itself an inner-product identification. No Hilbert representation theorem is used here.

5 · Examples, counterexamples and false statements

ExampleConstruction: AI-generatedVerification: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-07Open item page →

Coordinate functionals on sequence spaces

Example

Let K=R or C. For every n0, the coordinate functional πn:xxn has norm one on both c0(K) and 1(K). Under their sequence-dual identifications it is represented by en.

Facts & Assumptions

Given: The spaces, maps, scalar field, and hypotheses in the statement above. All duals consist of linear functionals over the ambient field; evaluation has no conjugation.

[F1]

From The continuous dual of c0 is ell-one, with its stated hypotheses: Let K=R or C. With coordinates starting at zero, the map 1(K)c0(K),afa,fa(x)=n=0anxn is a linear isometric bijection. The pairing is bilinear, including over C.

[F2]

From The complex continuous dual of ell-one is ell-infinity, with its stated hypotheses: For complex sequence spaces, with indices starting at zero, (C)1(C),bhb,hb(a)=n=0bnan is a complex-linear isometric bijection. There is no conjugation in this pairing.

[F3]

From Counting measure specializes the representation theorem to p and q, with its stated hypotheses: Let 1p< and let q be conjugate to p. Every bounded linear functional Λ:pR is of the form Λ(a)=n=0anbn for a unique sequence bq. Moreover, Λ=bq.

Verification

1.1

The pairing for c0 assigns to en1 the functional xxn. The complex 1 dual formula does the same for en, and the real counting-measure theorem at p=1 gives the real counterpart.

F1F2F3
2.1

On c0, xnx; on 1, xnx1. Thus each norm is at most one. In both spaces en=1 and πn(en)=1, proving equality. This works at index zero as well as every later index; the zero input gives zero.

step 1.1
ExampleConstruction: AI-generatedVerification: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-07Open item page →

Transposes of the right and left shifts

Example

Let K=R or C. On c0(K) or 1(K), define R(x0,x1,)=(0,x0,x1,),L(x0,x1,)=(x1,x2,). Under the dual pairing, the transposes on 1 (for domain c0) and on (for domain 1) satisfy R=L and L=R.

Facts & Assumptions

Given: The spaces, maps, scalar field, and hypotheses in the statement above. All duals consist of linear functionals over the ambient field; evaluation has no conjugation.

[F1]

From The transpose of a bounded operator, with its stated hypotheses: Let K=R or C. Let T:XY be bounded and linear between normed spaces. Its transpose, or Banach adjoint, is T:YX,(Tg)(x)=g(Tx). The duals are def-dual-space-of-a-normed-space. Composition is bounded by lem-composition-operator-norm-inequality, so this has the displayed codomain. It is linear in g over K. No complex conjugation is inserted; a Hilbert adjoint uses a separate inner-product identification.

[F2]

From The continuous dual of c0 is ell-one, with its stated hypotheses: Let K=R or C. With coordinates starting at zero, the map 1(K)c0(K),afa,fa(x)=n=0anxn is a linear isometric bijection. The pairing is bilinear, including over C.

[F3]

From The complex continuous dual of ell-one is ell-infinity, with its stated hypotheses: For complex sequence spaces, with indices starting at zero, (C)1(C),bhb,hb(a)=n=0bnan is a complex-linear isometric bijection. There is no conjugation in this pairing.

[F4]

From Counting measure specializes the representation theorem to p and q, with its stated hypotheses: Let 1p< and let q be conjugate to p. Every bounded linear functional Λ:pR is of the form Λ(a)=n=0anbn for a unique sequence bq. Moreover, Λ=bq.

Verification

1.1

Both shifts preserve null sequences; inserting or deleting a coordinate also preserves absolute summability and boundedness. Each is linear, R preserves the relevant norm, and L is contractive. This verifies that all displayed operators have the stated spaces as domain and codomain, including on zero inputs.

given
2.1

For xc0 and a1, the absolutely convergent pairings give n0an(Rx)n=n0an+1xn and n0an(Lx)n=n1an1xn. These are the pairings of La and Ra with x, respectively. Hence R=L and L=R on 1.

F1F2step 1.1
3.1

For x1 and bounded a, the same two series are absolutely convergent, since their absolute sums are at most ax1. The complex dual identification, or the real counting-measure identification at p=1, therefore gives the same transpose formulas on . The inserted zeroth coordinate is essential in the formula for Ra.

F1F3F4step 1.1step 2.1
ExampleConstruction: AI-adaptedVerification: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-07Open item page →

Evaluation functionals and point masses

Example

Let K be a nonempty compact Hausdorff space and tK. On C(K;C) with supremum norm, δt(f)=f(t) has norm one and is represented by the regular point mass at t. If ϕ:KK is a homeomorphism and Pf=fϕ, then Pδt=δϕ(t).

Facts & Assumptions

Given: The spaces, maps, scalar field, and hypotheses in the statement above. All duals consist of linear functionals over the ambient field; evaluation has no conjugation.

[F1]

From The transpose of a bounded operator, with its stated hypotheses: Let K=R or C. Let T:XY be bounded and linear between normed spaces. Its transpose, or Banach adjoint, is T:YX,(Tg)(x)=g(Tx). The duals are def-dual-space-of-a-normed-space. Composition is bounded by lem-composition-operator-norm-inequality, so this has the displayed codomain. It is linear in g over K. No complex conjugation is inserted; a Hilbert adjoint uses a separate inner-product identification.

[F2]

From The bounded complex dual of C_0(X) is regular complex measures, with its stated hypotheses: For an LCH space X, every bounded complex linear functional L on C0(X;C) has a unique representation L(f)=Xfdμ by a finite regular complex Borel measure μ. Conversely each such μ defines a bounded functional and L=μ(X).

Verification

1.1

Evaluation is complex-linear and f(t)f. The continuous constant function 1 has norm one since K, and δt(1)=1, so δt=1.

given
1.2

Define the Borel measure μt(A)=1 when tA and 0 otherwise. In a disjoint countable union at most one member contains t, proving countable additivity. Its mass is one. For inner regularity, a set containing t contains the compact singleton {t}, and a set not containing t has measure zero. For outer regularity, a set missing t lies in the open set K{t} of measure zero; for a set containing t, every open superset has measure one.

given
2.1

Integration of a simple Borel function against μt equals its value at t. Uniform simple approximation of a bounded complex Borel function extends this identity, since the integral error is bounded by the uniform error times μt(K)=1. In particular fdμt=f(t) for fC(K;C). Compact Hausdorff K is LCH and C0(K)=C(K), so RMK uniqueness identifies this regular point mass as the representing measure.

F2step 1.1step 1.2
3.1

Composition with a homeomorphism preserves continuity and the supremum norm. For every f, (Pδt)(f)=δt(fϕ)=f(ϕ(t))=δϕ(t)(f), which proves the transpose identity.

F1step 1.1
ExampleConstruction: AI-generatedVerification: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-07Open item page →

The annihilator of a coordinate subspace

Example

Let K=R or C. For IN, put MI={xc0(K):xn=0 for nI}. It is closed, and under c0=1 its annihilator is AI={a1(K):an=0 for nI}. The preannihilator AI is MI.

Facts & Assumptions

Given: The spaces, maps, scalar field, and hypotheses in the statement above. All duals consist of linear functionals over the ambient field; evaluation has no conjugation.

[F1]

From Annihilator notation and the preannihilator, with its stated hypotheses: Let K=R or C. For a normed X and arbitrary subsets MX, NX, define M={fX:f(m)=0 for all mM},N={xX:f(x)=0 for all fN}. Here X is def-dual-space-of-a-normed-space. The first notation agrees with def-continuous-annihilator-of-a-subspace on spanM, since linearity makes vanishing on M equivalent to vanishing on its span. The preannihilator lies in X, not in X. Empty sets impose no conditions: =X and =X.

[F2]

From The continuous dual of c0 is ell-one, with its stated hypotheses: Let K=R or C. With coordinates starting at zero, the map 1(K)c0(K),afa,fa(x)=n=0anxn is a linear isometric bijection. The pairing is bilinear, including over C.

Verification

1.1

Each coordinate map on c0 is continuous since xnx. Thus MI is the intersection of the closed coordinate kernels for nI, hence is closed and linear. If a annihilates MI, testing enMI for nI gives an=0.

F1F2
2.1

Conversely if an=0 on I and xMI, every product anxn is zero, so the absolutely convergent pairing vanishes. This proves MI=AI.

F1F2step 1.1
3.1

If x annihilates AI, testing enAI for nI gives xn=0, hence xMI. The converse follows again because every coordinate product vanishes. For I=, (MI,AI)=(0,1); for I=N it is (c0,0), with the same test arguments.

F1F2step 2.1
ExampleConstruction: AI-adaptedVerification: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-07Open item page →

Finite-dimensional duals and matrix transposes

Example

Let K=R or C. Let X,Y be finite-dimensional normed spaces with fixed ordered bases. Their continuous duals equal their algebraic duals. If T:XY has matrix A=(Aij) in these bases, then T:YX has matrix At in the dual bases, even over C.

Facts & Assumptions

Given: The spaces, maps, scalar field, and hypotheses in the statement above. All duals consist of linear functionals over the ambient field; evaluation has no conjugation.

[F1]

From The transpose of a bounded operator, with its stated hypotheses: Let K=R or C. Let T:XY be bounded and linear between normed spaces. Its transpose, or Banach adjoint, is T:YX,(Tg)(x)=g(Tx). The duals are def-dual-space-of-a-normed-space. Composition is bounded by lem-composition-operator-norm-inequality, so this has the displayed codomain. It is linear in g over K. No complex conjugation is inserted; a Hilbert adjoint uses a separate inner-product identification.

[F2]

From The dual family of a finite basis is a basis of the dual space, with the same dimension, with its stated hypotheses: If B=(b1,,bn) is a basis of a finite-dimensional F-vector space V, then its dual family B=(b1,,bn) is a basis of V. Consequently dimV=dimV=n.

[F3]

From A linear map from a finite-dimensional normed space is bounded, with its stated hypotheses: Let X and Y be normed spaces over the same scalar field, and assume X admits an ordered basis of finite length. Then every linear map S:XY is a bounded linear operator in the sense of def-bounded-linear-operator.

Verification

1.1

Every algebraic linear functional on X or Y is bounded, since its domain has a fixed finite basis and its scalar codomain is normed. Conversely a continuous-dual functional is algebraically linear by definition. The dual families are bases of these duals.

F2F3
2.1

Writing x=jxjej and g=igifi gives (Tg)(x)=g(Tx)=igijAijxj=j(iAijgi)xj. Thus the dual-coordinate column is Atg. The computation is bilinear, without conjugation.

F1F2step 1.1
3.1

If either dimension is zero, the corresponding sums are empty and define the unique zero map with its appropriate rectangular matrix. In dimension one the transpose leaves the scalar entry unchanged, including a nonreal scalar.

step 2.1
CounterexampleConstruction: AI-generatedVerification: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-07Open item page →

The dual construction reverses arrows

Statement refuted

Let K=R or C. The proposed composition rule “a bounded T:XY induces XY by composition” has the wrong direction. For the inclusion i:KK2, i(t)=(t,0), composition instead gives restriction i:(K2)K.

Facts & Assumptions

Given: The spaces, maps, scalar field, and hypotheses in the statement above. All duals consist of linear functionals over the ambient field; evaluation has no conjugation.

[F1]

From The transpose of a bounded operator, with its stated hypotheses: Let K=R or C. Let T:XY be bounded and linear between normed spaces. Its transpose, or Banach adjoint, is T:YX,(Tg)(x)=g(Tx). The duals are def-dual-space-of-a-normed-space. Composition is bounded by lem-composition-operator-norm-inequality, so this has the displayed codomain. It is linear in g over K. No complex conjugation is inserted; a Hilbert adjoint uses a separate inner-product identification.

[F2]

From Transposition reverses composition, with its stated hypotheses: Let K=R or C. For bounded linear T:XY, S:YZ between normed spaces, (ST)=TS,IX=IX. For bounded T,U:XY and a,bK, (aT+bU)=aT+bU.

Counterexample

1.1

Use the usual scalar norm and the maximum norm on K2, so i is bounded. The functional ga,b(s,t)=as+bt is bounded by ga,b(s,t)(a+b)max(s,t). Composition gives (iga,b)(t)=ga,b(t,0)=at.

F1
2.1

A functional f:KK cannot be composed as fi to produce a functional on K2: the output of i has the wrong type for the input of f, and the composite would in any event have domain K. The valid composition reverses arrows, as also expressed by (ST)=TS. Setting a=0,b=1 in step 1.1 even gives a nonzero functional whose restriction is zero. This refutes the proposed composition rule, without claiming every conceivable covariant assignment is impossible.

F2step 1.1
CounterexampleConstruction: AI-generatedVerification: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-07Open item page →

The canonical bidual map of c0 misses the constant sequence

Statement refuted

Let K=R or C. A canonical bidual embedding need not be onto. Under the sequence-dual identifications, Jc0:c0(K)c0(K) is the inclusion c0(K)(K), and the constant sequence (1,1,) is outside its image.

Facts & Assumptions

Given: The spaces, maps, scalar field, and hypotheses in the statement above. All duals consist of linear functionals over the ambient field; evaluation has no conjugation.

[F1]

From The continuous dual of c0 is ell-one, with its stated hypotheses: Let K=R or C. With coordinates starting at zero, the map 1(K)c0(K),afa,fa(x)=n=0anxn is a linear isometric bijection. The pairing is bilinear, including over C.

[F2]

From The complex continuous dual of ell-one is ell-infinity, with its stated hypotheses: For complex sequence spaces, with indices starting at zero, (C)1(C),bhb,hb(a)=n=0bnan is a complex-linear isometric bijection. There is no conjugation in this pairing.

[F3]

From Counting measure specializes the representation theorem to p and q, with its stated hypotheses: Let 1p< and let q be conjugate to p. Every bounded linear functional Λ:pR is of the form Λ(a)=n=0anbn for a unique sequence bq. Moreover, Λ=bq.

[F4]

From The canonical evaluation map into the bidual, with its stated hypotheses: Let K=R or C. For a normed X, define JX:XX,(JXx)(f)=f(x)(fX). With the dual norm from def-dual-space-of-a-normed-space, evaluation is linear in f and (JXx)(f)xf, so JXx is a bounded functional on X. The map is canonical and uses no chosen basis or conjugation.

Counterexample

1.1

The first dual is identified isometrically with 1 through afa, where fa(x)=nanxn. Its dual is , by the complex endpoint theorem or the real counting-measure theorem at p=1. Precomposition with a surjective isometry preserves functional norms and is bijective by precomposition with its inverse, so these identifications also identify the bidual.

F1F2F3
2.1

By canonical evaluation, (Jc0x)(fa)=fa(x)=nanxn, whose coefficient sequence in is exactly x. The constant-one sequence is bounded, but a preimage would have xn=1 for every n, as tested with a=en. Such a sequence does not tend to zero. Thus the named canonical map is not onto. Its zero input maps to zero, so the obstruction is the specified nonzero element.

F4step 1.1
CounterexampleConstruction: AI-adaptedVerification: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-07Open item page →

The transpose of an injective map need not have norm-dense range

Statement refuted

An injective bounded operator need not have norm-dense transpose range. Over R, take the inclusion T:1c0. Its transpose is the inclusion T:1, and ranT=c0=(kerT). The operator T is injective and has dense range.

Facts & Assumptions

Given: The spaces, maps, scalar field, and hypotheses in the statement above. All duals consist of linear functionals over the ambient field; evaluation has no conjugation.

[F1]

From The transpose of a bounded operator, with its stated hypotheses: Let K=R or C. Let T:XY be bounded and linear between normed spaces. Its transpose, or Banach adjoint, is T:YX,(Tg)(x)=g(Tx). The duals are def-dual-space-of-a-normed-space. Composition is bounded by lem-composition-operator-norm-inequality, so this has the displayed codomain. It is linear in g over K. No complex conjugation is inserted; a Hilbert adjoint uses a separate inner-product identification.

[F2]

From The continuous dual of c0 is ell-one, with its stated hypotheses: Let K=R or C. With coordinates starting at zero, the map 1(K)c0(K),afa,fa(x)=n=0anxn is a linear isometric bijection. The pairing is bilinear, including over C.

[F3]

From Counting measure specializes the representation theorem to p and q, with its stated hypotheses: Let 1p< and let q be conjugate to p. Every bounded linear functional Λ:pR is of the form Λ(a)=n=0anbn for a unique sequence bq. Moreover, Λ=bq.

[F4]

From Finite truncations approximate null and summable sequences, with its stated hypotheses: Let K=R or C. Use coordinates indexed by N={0,1,}. Define 1(K)={a:n=0an<}, with coordinatewise operations and norm a1=nan. Let PN retain coordinates 0,,N and set all others to zero. Then xPNx0(xc0(K)),aPNa10(a1(K)).

[F5]

From c_0 is a closed subspace of ell-infinity, with its stated hypotheses: c0 is a closed linear subspace of in the sup norm.

[F6]

From Annihilator notation and the preannihilator, with its stated hypotheses: Let K=R or C. For a normed X and arbitrary subsets MX, NX, define M={fX:f(m)=0 for all mM},N={xX:f(x)=0 for all fN}. Here X is def-dual-space-of-a-normed-space. The first notation agrees with def-continuous-annihilator-of-a-subspace on spanM, since linearity makes vanishing on M equivalent to vanishing on its span. The preannihilator lies in X, not in X. Empty sets impose no conditions: =X and =X.

Counterexample

1.1

Absolute summability implies convergence to zero: infinitely many coordinates of magnitude at least ε>0 would make partial absolute sums unbounded. Also xx1, so inclusion is bounded and injective. Finite-support sequences lie in its range and are dense in c0 by truncation.

F4
1.2

Identify c0 with 1 and (1) with real . For a1 and x1, (Tfa)(x)=fa(Tx)=nanxn, so the transpose corresponds to the same coefficient sequence a, now viewed in .

F1F2F3
2.1

The transpose image is contained in c0, which is closed in , so its norm closure is contained in c0. Conversely it contains all finite-support sequences, whose sup-norm closure contains c0 by truncation. Hence that closure is exactly c0.

F4F5step 1.1step 1.2
3.1

The constant-one sequence has distance exactly one from c0: for zn0, 1zn1, so 1z1, and z=0 attains one. It is therefore outside the closure. Since kerT=0, its annihilator is all of (1)=, proving strict inclusion.

F6step 1.1step 2.1
CounterexampleConstruction: AI-adaptedVerification: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-07Open item page →

Injective transpose does not imply surjectivity

Statement refuted

An injective transpose does not force surjectivity of the original bounded operator. On real 2, define (Tx)n=xnn+1(n0). Under the real counting-measure dual identification, T=T. Both maps are injective with dense nonclosed range, and neither is onto.

Facts & Assumptions

Given: The spaces, maps, scalar field, and hypotheses in the statement above. All duals consist of linear functionals over the ambient field; evaluation has no conjugation.

[F1]

From The transpose of a bounded operator, with its stated hypotheses: Let K=R or C. Let T:XY be bounded and linear between normed spaces. Its transpose, or Banach adjoint, is T:YX,(Tg)(x)=g(Tx). The duals are def-dual-space-of-a-normed-space. Composition is bounded by lem-composition-operator-norm-inequality, so this has the displayed codomain. It is linear in g over K. No complex conjugation is inserted; a Hilbert adjoint uses a separate inner-product identification.

[F2]

From Counting measure specializes the representation theorem to p and q, with its stated hypotheses: Let 1p< and let q be conjugate to p. Every bounded linear functional Λ:pR is of the form Λ(a)=n=0anbn for a unique sequence bq. Moreover, Λ=bq.

[F3]

From p is the Lp space of counting measure, with its stated hypotheses: On (N,P(N),#) with counting measure, every function f:NR is measurable. Writing ak:=f(k), one has fpd#=k=0akp(0<p<), by the counting-measure integral dictionary, so Lp(#) is exactly the usual sequence class p. Also f=supkNak, because a subset of N has counting measure zero only when it is empty. Hence the quotient by almost-everywhere equality does nothing: for counting measure on N, equality almost everywhere means equality everywhere.

Counterexample

1.1

The real counting-measure model has x22=nxn2. Thus Tx2x2 and T is linear and injective. Every finite-support y has the finite-support preimage xn=(n+1)yn; truncating a square-summable sequence approximates it because the squared tail sums tend to zero. Therefore the range is dense.

F3
2.1

For a,x2, the pairing is nanxn. Absolute convergence follows, for example, from 2anxnan2+xn2. Hence (Ta)(x)=nanxn/(n+1)=n(Ta)nxn, and uniqueness in the real duality theorem at p=2 gives T=T.

F1F2step 1.1
3.1

The sequence yn=1/(n+1) lies in 2: the zeroth squared term is one and for n1, 1/(n+1)21/n1/(n+1), whose sums telescope. A preimage would satisfy xn=1 for all n, which is not square summable. Thus T is not onto and its dense range is proper, hence nonclosed. By step 2.1 the same is true of T. The formula is defined at index zero, and zero is in both ranges.

step 1.1step 2.1

Sources