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How statement and proof provenance work

The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.

  • Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
  • AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
  • AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.

These labels describe origin, not correctness: citations and verification chips remain separate evidence.

Hilbert Space Geometry and Riesz Representation

1 · Prerequisites

2 · Summary

The pair begins from the published definition of a real or complex inner product and the library's normed-space conventions, and it records the induced length as the published inner-product norm. Cauchy--Schwarz, the induced norm axioms, the parallelogram law and the Jordan--von Neumann polarisation characterisation are proved before any completeness is assumed, so the elementary geometry of the pairing is choice-free. Metric and product topology, the published real infimum machinery, the published completion of a normed space and the published countable-choice principle supply the analytic layer: the completion pairing is built from limits of pairings, and the closest-point theorem selects approximate minimisers, which is the exact place where Countable Choice is spent.

The page develops orthogonality, orthogonal complements, the closest point in a closed convex set with its variational characterisation, and the orthogonal decomposition of a Hilbert space by a closed subspace, from which the Hilbert orthogonal projection and its linearity, self-adjointness and contractivity follow. Riesz representation, the canonical reflexivity of Hilbert spaces, the Hilbert adjoint and its identities, the vocabulary of self-adjoint, positive, unitary and normal operators, and the kernel--range orthogonality of adjoints form the second half. The closing remarks record the agreement with the concrete projection construction and the ownership boundary that leaves Lax--Milgram to the partial-differential-equations track.

3 · Logical flowchart

4 · Definitions, theorems and proofs

DefinitionDefinition: AI-adaptedProof: Not applicableaudited 2026-09-22Open item page →

Real and complex inner-product spaces and their induced length

Definition

Let F be R or C, with conjugation zz the identity on R and complex conjugation on C (Real and imaginary parts, complex conjugation, and modulus). A real or complex inner-product space is an F-vector space V together with an inner product ,:V×VF in the sense of Real and complex inner product spaces, with the inner product linear in the first argument: for all u,v,wV and a,bF,

au+bv,w=au,w+bv,w,u,v=v,u,v,v0,v,v=0    v=0.

Conjugate-linearity in the second argument. Conjugate symmetry together with linearity in the first argument gives, for all wV,

w,au+bv=au+bv,w=au,w+bv,w=aw,u+bw,v.

Induced length. The induced length, or inner-product norm, of v is

v:=v,v,

which is exactly the published The norm v=v,v induced by a real or complex inner product: positive definiteness makes v,v a nonnegative real with a unique nonnegative square root, so that v0, v=0 exactly for v=0, and v,v=v2.

The convention on this page. Every inner-product space below is real or complex in this sense, the pairing is linear in the first argument and conjugate-linear in the second, and v always denotes the induced length. In the real case conjugation is the identity and z is the absolute value of R; in the complex case they are complex conjugation and the complex modulus. All statements below are therefore written once and read in either scalar field.

TheoremStatement: AI-adaptedProof: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-22Open item page →

Cauchy–Schwarz: x,yxy, with equality exactly for dependent pairs

Statement

For all vectors x,y in a real or complex inner-product space,

x,yxy,

with equality if and only if x and y are linearly dependent.

Facts & Assumptions

[A1]

The pairing is linear in the first argument, conjugate-linear in the second, conjugate symmetric and positive definite, and the induced length satisfies v,v=v2 with v0 and v=0 exactly for v=0 (Real and complex inner-product spaces and their induced length).

[A2]

The induced length is the unique nonnegative square root of the diagonal pairing, and positive definiteness makes the radicand a nonnegative real (The norm v=v,v induced by a real or complex inner product).

[A3]

Every nonnegative real has a unique nonnegative square root: there is exactly one s0 with sn=a for each n1 (Existence and uniqueness of n-th roots: a unique a1/n0 with (a1/n)n=a).

[A4]

For complex scalars zz=z2, z0, and z=0 exactly for z=0 (Conjugation is an involutive real-field automorphism, zz=z2, and modulus is definite, multiplicative, and subadditive).

[A5]

For real scalars x0, x=0 exactly for x=0, and xy=xy (Basic properties of the absolute value).

[A6]

For nonnegative reals, ab if and only if a2b2 (Squaring is monotone on the nonnegatives).

[A7]

A finite list is linearly dependent when some choice of scalars, not all zero, makes the corresponding combination vanish; for the two-element list (x,y) this means that ax+by=0 for scalars a,b not both zero (Linear independence: a finite list v:nV is independent when i<nλivi=0V forces every λi=0F, and a subset SV is independent when every injective finite list into S is independent).

Proof

technique · direct

Given: Vectors x,y in a real or complex inner-product space V. In the real case read conjugation as the identity and as the absolute value of R, so that [A4] is replaced by [A5].

1.1

If y=0, then x,y=x,0y=0x,y=0 by conjugate-linearity in the second argument, and y=0; hence x,y=0=xy, while x,y are dependent with witness scalars (a,b)=(0,1) because 0x+10=0 and b0.

A1A2A7
1.2

Suppose now y0 and set c=x,y/y,y, a well-defined scalar because y,y=y2>0; expanding with linearity in the first argument, conjugate-linearity in the second and conjugate symmetry gives 0xcy2=x2cx,ycx,y+c2y2=x2x,y2/y2.

A1A2A3A4A5algebra
2.1

Multiplying step 1.2 by the positive number y2 gives x,y2x2y2, and since x,y, x and y are nonnegative, monotonicity of squaring on the nonnegatives gives the inequality x,yxy.

A2A6step 1.2algebra
2.2

If x,y are dependent, then either y=0, which is step 1.1, or x=cy for some scalar c with y0; in the second case x,y=cy2 and cy2=cy,cy=c2y2 with both norms nonnegative, so x=cy by uniqueness of nonnegative square roots, and x,y=cy2=xy.

A1A2A3A4A5A6A7step 1.1algebra
3.1

Conversely suppose x,y=xy and y0; then y2>0 and step 1.2 gives xcy2=x2x2=0, so xcy=0 by positive definiteness, that is x=cy and the pair is dependent by [A7]; together with steps 1.1 and 2.2 this proves the inequality and both directions of the equality statement.

A1A7step 1.1step 1.2step 2.2
CorollaryStatement: AI-adaptedProof: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-22Open item page →

The induced length is a norm

Statement

Let V be a real or complex inner-product space with induced length v=v,v. Then v0 with v=0 exactly for v=0, λv=λv for every scalar λ, and u+vu+v; hence is a norm on V, read over R by A norm on a real vector space, the induced metric, and the dictionary with the metric axioms and over C by Real and complex scalar conventions for normed spaces.

Facts & Assumptions

[A1]

The induced length is the unique nonnegative square root of the diagonal pairing, with v0 and v=0 exactly for v=0 (The norm v=v,v induced by a real or complex inner product).

[A2]

Cauchy–Schwarz gives u,vuv (Cauchy–Schwarz: x,yxy, with equality exactly for dependent pairs).

[A3]

A norm on a real vector space satisfies separation, absolute homogeneity and the triangle inequality, and a complex normed space is defined by the same clauses with the complex modulus (A norm on a real vector space, the induced metric, and the dictionary with the metric axioms, Real and complex scalar conventions for normed spaces).

[A4]

For complex scalars zz=z2 and λλ=λ2 (Conjugation is an involutive real-field automorphism, zz=z2, and modulus is definite, multiplicative, and subadditive), and for real scalars xy=xy with x0 (Basic properties of the absolute value).

[A5]

For nonnegative reals ab if and only if a2b2 (Squaring is monotone on the nonnegatives), and each nonnegative real has a unique nonnegative square root (Existence and uniqueness of n-th roots: a unique a1/n0 with (a1/n)n=a).

[A6]

If z=a+bi then Rez=a and z=a2+b2, so Rezz (Real and imaginary parts, complex conjugation, and modulus).

Proof

technique · direct

Given: A real or complex inner-product space V, vectors u,vV and a scalar λ; in the real case conjugation is the identity and is the absolute value of R, so the second clause of [A4] is read in the real field.

1.1

Nonnegativity and separation are [A1]: v0, and v=0 exactly when v,v=0, that is exactly when v=0.

A1A3
1.2

Homogeneity: λv,λv=λλv,v=λ2v2 by sesquilinearity and [A4], and both λv and λv are nonnegative with equal squares, so λv=λv by uniqueness of the nonnegative square root.

A1A4A5algebra
1.3

Triangle inequality: expanding and using conjugate symmetry gives u+v2=u2+2Reu,v+v2, and Rezz for every scalar z, since either Rez<0z or Rez=a0 with a2a2+b2=z2 by [A6]; with [A2] this gives u+v2u2+2uv+v2=(u+v)2.

A1A2A4A6algebra
2.1

Both sides of the inequality in step 1.3 are nonnegative, so monotonicity of squaring on the nonnegatives turns it into u+vu+v.

A5step 1.3
3.1

Steps 1.1, 1.2 and 2.1 are exactly the clauses of [A3] over R, and over C they are the same clauses with the complex modulus, so is a norm on V in either scalar field.

A3step 1.1step 1.2step 2.1
TheoremStatement: AI-adaptedProof: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-22Open item page →

The parallelogram law

Statement

In every real or complex inner-product space, for all vectors x,y,

x+y2+xy2=2x2+2y2.

Facts & Assumptions

[A1]

The pairing is linear in the first argument, conjugate-linear in the second and conjugate symmetric, and v2=v,v (Real and complex inner-product spaces and their induced length).

[A2]

The induced length is the unique nonnegative square root of the diagonal pairing, so v2=v,v (The norm v=v,v induced by a real or complex inner product).

Proof

technique · direct

Given: Vectors x,y in a real or complex inner-product space.

1.1

Expanding with linearity in the first argument, conjugate-linearity in the second and conjugate symmetry gives x+y2=x+y,x+y=x2+x,y+x,y+y2 and, replacing y by y, xy2=x2x,yx,y+y2.

A1A2algebra
2.1

The cross terms in step 1.1 cancel when the two expansions are added, so x+y2+xy2=2x2+2y2, the parallelogram law.

step 1.1algebra
TheoremStatement: AI-adaptedProof: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-22Open item page →

Jordan–von Neumann: a norm is induced by an inner product exactly when it satisfies the parallelogram law

Statement

Let V be a real or complex vector space with a norm . Then is induced by an inner product on V if and only if it satisfies the parallelogram law

x+y2+xy2=2x2+2y2(x,yV).

In that case the inner product is unique, and it is given by the real polarisation formula

x,y=14(x+y2xy2)

in the real case, and by the complex polarisation formula

x,y=14(x+y2xy2+ix+iy2ixiy2)

in the complex case with the first-variable-linear convention.

Facts & Assumptions

[A1]

In a real or complex inner-product space the pairing is linear in the first argument, conjugate-linear in the second, conjugate symmetric and positive definite, and v2=v,v (Real and complex inner-product spaces and their induced length).

[A2]

The induced length is the unique nonnegative square root of the diagonal pairing (The norm v=v,v induced by a real or complex inner product).

[A3]

A norm satisfies q(λz)=λ2q(z) for q(z)=z2, in particular q(0)=0, q(z)=q(z) and q(iz)=q(z) in the complex case, and it satisfies the triangle inequality; complex normed spaces follow the scalar convention of the remark (A norm on a real vector space, the induced metric, and the dictionary with the metric axioms, Real and complex scalar conventions for normed spaces).

[A4]

Every real or complex inner-product norm satisfies the parallelogram law (The parallelogram law).

[A5]

Every real number is approximated by rationals: for xR and rational ε>0 there is a rational q with xq<ε (The rationals embed densely in the reals).

[A6]

For every real ε>0 there is a natural n1 with 1/n<ε (For every ε>0 in a complete ordered field there is a natural n1 with 1/n<ε).

[A7]

For complex scalars z2=zz, z0, and i=1 (Conjugation is an involutive real-field automorphism, zz=z2, and modulus is definite, multiplicative, and subadditive).

[A8]

For nonnegative reals ab if and only if a2b2; every nonnegative real has a unique nonnegative square root (Squaring is monotone on the nonnegatives, Square roots exist: a unique a0 with (a)2=a; the positives are {x2:x0}).

Proof

technique · direct

Given: A real or complex vector space V with a norm ; write q(z)=z2. The real case is proved first, then the complex case, and finally necessity.

1.1

Assume first that V is real and satisfies the parallelogram law, and define b(x,y)=14(q(x+y)q(xy)); then b(x,x)=q(x), b(y,x)=b(x,y), b(x,y)=b(x,y)=b(x,y), b(0,y)=0, and q(λz)=λ2q(z) for real λ.

A3A4algebra
1.2

Applying the parallelogram law to the four pairs (p+q,r), (pq,r), (p+r,q) and (pr,q) and subtracting the fourth identity from the third gives 8b(p,r)=4b(p+q,r)+4b(pq,r), that is b(p+q,r)+b(pq,r)=2b(p,r) for all p,q,r.

A4algebra
2.1

Adding that identity at (p,q)=(u,v) and at (p,q)=(v,u) gives b(u+v,w)+b(vu,w)=2b(v,w) and b(u+v,w)+b(uv,w)=2b(u,w); since b(vu,w)=b(uv,w) by step 1.1, the two relations add to 2b(u+v,w)=2b(u,w)+2b(v,w), so b(u+v,w)=b(u,w)+b(v,w), and symmetry gives additivity in the second argument as well.

step 1.2step 1.1algebra
3.1

Induction on the natural number n0 using step 2.1 gives b(nx,y)=nb(x,y), and b(x,y)=b(x,y) is step 1.1, so b(mx,y)=mb(x,y) for every integer m.

step 2.1step 1.1algebra
4.1

For n1 the additivity of step 2.1 gives nb(x/n,y)=b(x,y), so b(x/n,y)=b(x,y)/n, and together with step 3.1 this yields b(rx,y)=rb(x,y) for every rational r.

step 3.1step 2.1algebra
5.1

Consequently for every rational t the form b is a symmetric rational-bilinear pairing with b(w+ty,w+ty)=b(w,w)+2tb(w,y)+t2b(y,y), that is q(w+ty)=q(w)+2tb(w,y)+t2q(y) by steps 1.1 and 4.1.

step 4.1step 1.1algebra
6.1

If q(y)>0, put C=q(w)b(w,y)2/q(y) and t=b(w,y)/q(y), so that step 5.1 reads q(y)(tt)2+C0 for every rational t; rationals approach t within any δ>0 by [A5], whence C>q(y)δ2 for every δ>0, and C0 because a negative C would give q(y)δ2<C for some δ>0 by [A6]; if instead q(y)=0 then q(w)+2tb(w,y)0 for all rational t forces b(w,y)=0, since otherwise [A6] supplies a rational t with 2tb(w,y)<q(w); in both cases b(w,y)2q(w)q(y), so b(w,y)wy by [A8].

step 5.1A5A6A8algebra
7.1

For fixed x,y the map φ(λ)=b(λx,y) is additive in λ by step 2.1 and satisfies φ(λ)λxy by step 6.1, hence φ(h)xy for h1; given ε>0 choose n1 with xy/n<ε by [A6], then h1/n gives φ(h)=φ(nh)/nxy/n<ε, so φ is continuous at 0.

step 2.1step 6.1A6algebra
8.1

For real λ and rational r one has φ(λ)λφ(1)φ(λr)+rλφ(1) with φ(r)=rφ(1) by step 4.1, so continuity at 0 from step 7.1 and the rational approximation of λ from [A5] give φ(λ)=λφ(1), that is b(λx,y)=λb(x,y) for every real λ.

step 7.1step 4.1A5algebra
9.1

Therefore, in the real case, b is symmetric, additive in each argument and real-homogeneous in the first argument, with b(x,x)=q(x)0 and b(x,x)=0 exactly for x=0; so b is a real inner product on V whose induced length is the given norm x=b(x,x).

step 1.1step 2.1step 8.1A1A2A3algebra
10.1

Now let V be complex with a norm satisfying the parallelogram law; viewing V as a real vector space with the same norm, to which step 9.1 applies, gives a real inner product b with b(x,x)=q(x), and q(iz)=q(z) together with the definition of b gives b(iu,iv)=b(u,v), hence b(iu,v)=b(u,iv) by the argument b(iu,v)=b(i(iu),iv)=b(u,iv)=b(u,iv).

step 9.1A3A7algebra
11.1

Define x,y=b(x,y)ib(ix,y); then additivity in both arguments and ix,y=ix,y follow from the real bilinearity of b, and conjugate symmetry y,x=x,y follows from b(y,x)=b(x,y) and from b(iy,x)=b(y,ix)=b(ix,y) in step 10.1.

step 10.1algebra
12.1

Positivity: x,x=b(x,x)ib(ix,x)=q(x) because b(ix,x)=b(x,ix) and b(x,ix)=b(ix,x) force b(ix,x)=0; hence , is a complex inner product whose induced length is x, and expanding b in terms of q gives the complex polarisation formula x,y=14(q(x+y)q(xy)+iq(x+iy)iq(xiy)).

step 11.1step 10.1A1A2A7algebra
13.1

Conversely, if the given norm is induced by an inner product on V, then it satisfies the parallelogram law by [A4] and expanding the pairing in terms of q recovers, in the real case, x,y=14(q(x+y)q(xy))=b(x,y) and, in the complex case, the four-term formula of step 12.1; with steps 9.1 and 12.1 this proves that a real or complex norm is induced by an inner product exactly when it satisfies the parallelogram law, and that the polarisation formulas display that inner product.

A1A2A4step 9.1step 12.1
DefinitionDefinition: AI-adaptedProof: Not applicableaudited 2026-09-22Open item page →

Hilbert space

Definition

A real Hilbert space is a real inner-product space H (Real and complex inner-product spaces and their induced length) whose induced-length metric is complete in the sense of Complete metric space: every Cauchy sequence converges in the space: every Cauchy sequence in H for the norm v=v,v (The induced length is a norm) converges to a point of H. A complex Hilbert space is a complex inner-product space with the same completeness property, so that a Hilbert space is exactly a real or complex inner-product space that is a Banach space for its induced norm (Banach space).

The completion convention is the Cauchy-sequence one. Banach space defines completeness by convergence of Cauchy sequences, and this page keeps that convention throughout. It is weaker than σ-completeness — the assertion that every decreasing sequence of nonempty closed subsets with diameters tending to zero has a nonempty intersection. The two agree in ZFC, but Blackadar, Farah and Karagila note that the closest-point theorem on a σ-complete inner-product space is provable in ZF, whereas the Cauchy-complete form used below consumes the Axiom of Countable Choice; nothing here silently imports the stronger notion.

LemmaStatement: AI-adaptedProof: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-22Open item page →

The inner product is jointly continuous

Statement

Let V be a real or complex inner-product space with induced norm . The pairing (x,y)x,y is continuous on V×V for the product of the induced norm topologies. Quantitatively, for all x,x,y,yV,

x,yx,yxxy+xyy,

and consequently xnx and yny in norm imply xn,ynx,y.

Facts & Assumptions

[A1]

The pairing is linear in the first argument and conjugate-linear in the second (Real and complex inner-product spaces and their induced length).

[A2]

Cauchy–Schwarz gives u,vuv (Cauchy–Schwarz: x,yxy, with equality exactly for dependent pairs).

[A3]

The induced length is a norm, so it is nonnegative, homogeneous and satisfies the triangle inequality (The induced length is a norm).

[A4]

In the metric topology a set is open exactly when every one of its points has a ball around it inside the set, B(x,r)={y:d(x,y)<r} is the open ball, and every open ball is open (The metric topology: a set is open when every one of its points has a ball around it inside the set; closed means open complement, Open ball, closed ball and sphere in a metric space, Arbitrary unions and finite intersections of open sets are open, open balls are open and closed balls are closed).

[A6]

Convergence in a metric space means that the distances to the limit tend to zero (Convergence of a sequence in a metric space: xkx iff d(xk,x)0 in R).

Proof

technique · direct

Given: A real or complex inner-product space V, vectors x,x,y,yV and a point of continuity (x,y) of V×V.

1.1

Inserting and subtracting the mixed pairing gives x,yx,y=xx,y+x,yy, so Cauchy–Schwarz applied to the two summands and the triangle inequality for scalars give x,yx,yxxy+xyy.

A1A2algebra
2.1

Given ε>0, put δ=min{1, ε/(1+x+y)}>0; if xx<δ and yy<δ, then yy+δ<1+y by the triangle inequality, so step 1.1 gives x,yx,y<δ(1+x+y)ε.

step 1.1A3algebra
3.1

The product B(x,δ)×B(y,δ) is a basic product-open set containing (x,y), and step 2.1 shows that on it the pairing stays within every ball about x,y, so the pairing is continuous at every point of V×V; if moreover xnx and yny, then for every ε>0 the pair (xn,yn) eventually lies in the corresponding δ-box, whence xn,ynx,y<ε and xn,ynx,y.

step 2.1A4A5A6
TheoremStatement: AI-adaptedProof: AI-adaptedaudited 2026-09-22Open item page →

The norm completion of an inner-product space is a Hilbert space

Statement

Assume the Axiom of Countable Choice. Let X be a real or complex inner-product space and let (X^,κ) be its norm completion (Completion of a normed space). Then X^ carries a unique inner product that extends the given one along κ and whose induced length is the completion norm; with it X^ is a Hilbert space, and the extension is unique among inner products that extend the given pairing and induce the completion norm.

Facts & Assumptions

[A1]

The completion (X^,κ) is a Banach space, κ:XX^ is a dense linear isometry, and X^ carries the unique compatible vector-space structure of the published metric completion (The metric completion of a normed space carries a unique compatible Banach-space structure, Completion of a normed space).

[A2]

The induced length of an inner-product space is a norm (The induced length is a norm). Conversely, a norm on a real or complex vector space is induced by an inner product if and only if it satisfies the parallelogram law. That inner product is unique and is recovered by the real or first-linear complex polarisation formula (Jordan–von Neumann: a norm is induced by an inner product exactly when it satisfies the parallelogram law).

[A3]

Cauchy–Schwarz holds in every inner-product space; the resulting two-variable difference estimate proves joint continuity (Cauchy–Schwarz: x,yxy, with equality exactly for dependent pairs, The inner product is jointly continuous).

[A4]

Vector addition and scalar multiplication are continuous, and uvuv (Vector addition and scalar multiplication are continuous in a normed space, The reverse triangle inequality in a normed space).

[A5]

Countable Choice selects a point from every member of a countable family of nonempty sets, and 1/(n+1)0 (The Axiom of Countable Choice (ACω), For every ε>0 in a complete ordered field there is a natural n1 with 1/n<ε).

[A6]

Every real or complex inner-product norm satisfies the parallelogram law (The parallelogram law).

[A7]

A Hilbert space is an inner-product space complete for its induced-norm metric (Hilbert space).

Proof

technique · direct

Given: Countable Choice, an inner-product space X with norm , and its norm completion (X^,κ) with completion norm also written .

1.1

Let ξ,ηX^. For every n, density makes the sets {xX:κxξ<1/(n+1)} and {yX:κyη<1/(n+1)} nonempty. Countable Choice selects xn,yn from these sets. Thus κ(xn)ξ and κ(yn)η, the selected sequences are Cauchy, and continuity of the vector operations gives κ(xn±yn)=κ(xn)±κ(yn)ξ±η.

A1A4A5
2.1

The parallelogram identities xn+yn2+xnyn2=2xn2+2yn2 hold in X by [A6]; passing to the limit using continuity of the norm and of sums, and the isometry κz=z, gives ξ+η2+ξη2=2ξ2+2η2, so the completion norm satisfies the parallelogram law.

step 1.1A1A4A6
3.1

The Jordan–von Neumann theorem applied to the Banach space X^ therefore produces an inner product B on X^ whose induced length is exactly the completion norm and which is the unique such inner product.

step 2.1A2A7
4.1

B extends the original pairing: for x,yX, the polarisation formula of [A2] together with κ(x±y)=κx±κy and the isometry property gives B(κx,κy)=14(κ(x+y)2κ(xy)2)=14(x+y2xy2)=x,y in the real case, and the four-term complex formula likewise in the complex case.

step 3.1A1A2
5.1

Uniqueness: if B is any inner product on X^ that extends the pairing along κ and induces the completion norm, then for ξ,η and approximating sequences as in step 1.1 the Cauchy–Schwarz inequality for both forms gives B(ξ,η)B(κxn,κyn)ξκxnη+κxnηκyn and the same bound for B, so both pairings are the limits of the common values xn,yn and B=B.

step 1.1step 4.1A1A3
6.1

Hence X^ carries the inner product B extending the original one with the completion norm as induced length, so it is complete and therefore a Hilbert space by [A7]. Countable Choice is used in the published completion interface and explicitly in step 1.1 to select the two approximating sequences; no further choice enters the limit arguments.

step 1.1step 3.1step 5.1A1A5A7
DefinitionDefinition: AI-adaptedProof: Not applicablejudge pass (gpt-5.6-terra)audited 2026-09-22Open item page →

Orthogonality and the orthogonal complement

Definition

Let V be a real or complex inner-product space. Vectors x,yV are orthogonal, written xy, when

x,y=0.

For a subset SV the orthogonal complement of S is

S:={vV:v,s=0 for every sS}.

Orthogonality is symmetric. If x,y=0, then y,x=x,y=0, so xy exactly when yx; in particular the condition defining S is symmetric in its two arguments.

S is a linear subspace. Let sS and scalars a,b; then 0,s=0, and if u,vS then au+bv,s=au,s+bv,s=0 by linearity in the first argument, so au+bvS. Thus S is a linear subspace of V (Linear subspace of a vector space) for every subset S, whether or not S is a subspace. Moreover 0S always, and vV lies in {0} for every v, so {0}=V.

Monotonicity. If STV, then every vector orthogonal to all of T is orthogonal to all of S, so TS.

Nontriviality of orthogonality. By positive definiteness v,v=v2=0 exactly for v=0 (The induced length is a norm), so a vector orthogonal to itself is zero, and {0}=V, V={0}.

LemmaStatement: AI-adaptedProof: AI-adaptedaudited 2026-09-22Open item page →

Pythagoras and finite orthogonal sums

Statement

Let x1,,xn be pairwise orthogonal vectors in a real or complex inner-product space, that is xi,xj=0 whenever ij (Orthogonality and the orthogonal complement). Then

j=1nxj2=j=1nxj2,

the empty sum on the right being 0 at n=0.

Facts & Assumptions

[A1]

Orthogonality means x,y=0, the pairing is linear in the first argument and conjugate-linear in the second, and v2=v,v (Orthogonality and the orthogonal complement, Real and complex inner-product spaces and their induced length).

[A2]

Every inner-product norm satisfies the parallelogram law (The parallelogram law).

Proof

technique · direct

Given: Pairwise orthogonal vectors x1,,xn in a real or complex inner-product space.

1.1

At n=0 the sum is 0 and both sides vanish, and at n=1 the identity is x12=x12.

A1
1.2

For two orthogonal vectors x,y, expansion gives x+y2=x2+x,y+y,x+y2=x2+y2, and the same computation with y replaced by y shows that the sum of a finite orthogonal family may be split off one term at a time.

A1A2algebra
2.1

Suppose the identity holds for orthogonal families of n1 terms, n2, and let x1,,xn be pairwise orthogonal; the partial sum s=j=1n1xj satisfies s,xn=j=1n1xj,xn=0 by linearity in the first argument, and s2=j=1n1xj2 by the induction hypothesis, so j=1nxj2=s+xn2=s2+xn2=j=1nxj2.

step 1.2step 1.1A1algebra
3.1

Induction on n from the cases n=0,1 of step 1.1 and the induction step of step 2.1 proves the identity for every n, so pairwise orthogonal vectors satisfy j=1nxj2=j=1nxj2.

step 1.1step 2.1
LemmaStatement: AI-adaptedProof: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-22Open item page →

Orthogonal complements are closed

Statement

For every subset S of a real or complex inner-product space V, the orthogonal complement S is a closed linear subspace of V for the induced norm topology.

Facts & Assumptions

[A1]

S={vV:v,s=0 for all sS} is a linear subspace and orthogonality is symmetric (Orthogonality and the orthogonal complement).

[A2]

Cauchy–Schwarz gives u,vuv (Cauchy–Schwarz: x,yxy, with equality exactly for dependent pairs).

[A3]

The induced length is a norm, so v0 with v=0 exactly for v=0 (The induced length is a norm).

[A4]

In the metric topology a set is open exactly when every point of it has a ball around it inside the set, and B(x,r)={y:d(x,y)<r} (The metric topology: a set is open when every one of its points has a ball around it inside the set; closed means open complement, Open ball, closed ball and sphere in a metric space).

Proof

technique · direct

Given: A subset S of a real or complex inner-product space V, with S as in [A1].

1.1

By [A1] the set S is a linear subspace of V, which is the first assertion.

A1
1.2

Let xS; then some sS has x,s0, so s0 and r=x,s/(2s)>0; if yV satisfies yx<r, then y,sx,sxy,s>x,srs=x,s/2>0 by Cauchy–Schwarz, so yS.

A1A2A3algebra
2.1

Thus every point outside S has a ball around it that misses S, so VS is open and S is closed in the metric topology; with step 1.1 this proves that S is a closed linear subspace.

step 1.1step 1.2A4
LemmaStatement: AI-adaptedProof: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-22Open item page →

A minimizing sequence in a convex set is Cauchy

Statement

Let C be a nonempty convex subset of a real or complex inner-product space, let x be a vector and put d=infcCxc. If cnC is a sequence with xcnd, then (cn) is a Cauchy sequence.

Facts & Assumptions

[A1]

A subset C is convex when (1t)u+tvC for all u,vC and 0t1 (Convex sets and continuous real-hyperplane separation in a normed space).

[A2]

If d=infS then ds for every sS (Greatest lower bound (infimum)).

[A3]

Every inner-product norm satisfies the parallelogram law (The parallelogram law).

[A4]

The norm is induced by the pairing, in particular uv is the distance between u and v and u+v=v+u (Real and complex inner-product spaces and their induced length).

Proof

technique · direct

Given: A nonempty convex set C, a vector x, the number d=infcCxc and a sequence cnC with xcnd.

1.1

Put un=xcn; for all m,n the midpoint (cm+cn)/2 lies in C by convexity, so 12(um+un)=x12(cm+cn)d because d is a lower bound of the distances from x to points of C.

A1A2A4
2.1

The parallelogram law applied to um,un gives umun2=2um2+2un2412(um+un)22um2+2un24d2.

step 1.1A3algebra
3.1

Given ε>0, convergence und provides N with 2un22d2<ε2/2 for all nN, and then step 2.1 gives cmcn2=umun2<ε2 for all m,nN; hence (cn) is Cauchy.

step 2.1algebra
TheoremStatement: AI-adaptedProof: AI-adaptedaudited 2026-09-22Open item page →

Projection onto a nonempty closed convex set

Statement

Assume the Axiom of Countable Choice. Let H be a real or complex Hilbert space, let CH be nonempty, closed and convex, and let xH. Then there is exactly one point pC with xp=infcCxc, that is, a unique nearest point of C to x.

Facts & Assumptions

[A1]

A Hilbert space is an inner-product space complete for its induced norm: every Cauchy sequence converges to a point of the space (Hilbert space).

[A2]

Every nonempty real set bounded below has an infimum, characterised by points arbitrarily close from above (Every nonempty set bounded below has an infimum, Epsilon characterisation of the infimum).

[A3]

Countable Choice selects a point from each set of a countable family of nonempty sets (The Axiom of Countable Choice (ACω)).

[A4]

A minimizing sequence in a nonempty convex set is Cauchy (A minimizing sequence in a convex set is Cauchy).

[A5]

C is convex and dxc for every cC (Convex sets and continuous real-hyperplane separation in a normed space, Greatest lower bound (infimum)). A closed set equals its closure, and a point lies in the closure whenever every ball about it meets the set (The closure of a nonempty A is {x:d(x,A)=0}, equals A together with its limit points, and is the smallest closed superset); limits in a metric space are unique (A sequence in a metric space has at most one limit).

[A6]

Norm distance is continuous: uvuv (The reverse triangle inequality in a normed space).

[A7]

Convergence of a sequence of reals to L means that for every ε>0 the terms are eventually within ε of L, and for every ε>0 some 1/n is below ε (Limits and Cauchy sequences of reals, For every ε>0 in a complete ordered field there is a natural n1 with 1/n<ε).

[A8]

Every inner-product norm satisfies the parallelogram law (The parallelogram law).

Proof

technique · direct

Given: Countable Choice, a real or complex Hilbert space H, a nonempty closed convex set CH and a vector xH.

1.1

The set D={xc:cC} is nonempty and bounded below by 0, so d=infD exists and for every n some cC has xc<d+1/(n+1) by the epsilon characterisation of the infimum.

A2
2.1

Countable Choice selects for every n a point cnC with xcn<d+1/(n+1), the sets being nonempty by step 1.1.

step 1.1A3
3.1

Then 0xcnd<1/(n+1) for every n, so xcnd by the Archimedean reciprocal bound; hence (cn) is Cauchy by the minimizing-sequence lemma, completeness of H gives a limit pH, and closedness of C places p in C.

step 2.1A1A4A5A7
4.1

Moreover xp=d: norm continuity along the limit gives xpxcnpcn0, and a limit of the sequence xcn is unique.

step 3.1A5A6
5.1

If p,qC both satisfy xp=xq=d, then the midpoint 12(p+q) lies in C by convexity, so x12(p+q)d, and the parallelogram law gives pq2=2xp2+2xq24x12(p+q)24d24d2=0, whence p=q: the nearest point is unique.

step 4.1A5A8algebra
TheoremStatement: AI-adaptedProof: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-22Open item page →

Variational characterisation of the nearest point

Statement

Assume the Axiom of Countable Choice. Let H be a real or complex Hilbert space, let CH be closed and convex with xH, and let pC. Then p is the nearest point of C to x if and only if

Rexp, yp0for every yC.

In particular, for the nearest point the inequality holds, and conversely any pC satisfying the inequality is nearest.

Facts & Assumptions

[A1]

C is convex: p+t(yp)C for yC and 0t1; and p is nearest exactly when xpxy for every yC (Convex sets and continuous real-hyperplane separation in a normed space).

[A2]

The pairing is linear in the first argument and conjugate-linear in the second, with v2=v,v (Real and complex inner-product spaces and their induced length).

[A3]

Countable Choice is the selection principle consumed by the existence theorem for nearest points (The Axiom of Countable Choice (ACω)).

Proof

technique · direct

Given: Countable Choice, a closed convex set C, a vector x and a point pC.

1.1

Suppose first that p is nearest, and let yC; for every t with 0<t1 the convexity hypothesis gives p+t(yp)C, so xp2xpt(yp)2=xp22tRexp,yp+t2yp2, whence 2Rexp,yptyp2, and if Rexp,yp were positive the choice t<min{1, 2Rexp,yp/(yp2+1)} would make the right-hand side strictly smaller than the left, a contradiction; hence Rexp,yp0.

A1A2algebra
1.2

Conversely suppose Rexp,yp0 for every yC; then xy2=(xp)+(py)2=xp2+2Rexp,py+py2xp2, because Rexp,py=Rexp,yp0.

A1A2algebra
2.1

Steps 1.1 and 1.2 prove both implications of the stated equivalence; the Countable Choice hypothesis is used only to invoke the existence theorem for nearest points (Projection onto a nonempty closed convex set) when the nearest point is not supplied, while the equivalence itself is choice-free for a given p.

step 1.1step 1.2A3
TheoremStatement: AI-adaptedProof: AI-adaptedaudited 2026-09-22Open item page →

Orthogonal decomposition by a closed subspace

Statement

Assume the Axiom of Countable Choice. Let M be a closed linear subspace of a real or complex Hilbert space H. Then every xH has a unique decomposition

x=m+n,mM,nM,

so that H=MM as a direct sum of the subspace M and its orthogonal complement.

Facts & Assumptions

[A1]

A linear subspace is convex and contains 0, and the nearest point of a nonempty closed convex subset of a Hilbert space exists and is unique (Linear subspace of a vector space, Projection onto a nonempty closed convex set).

[A2]

A point p is the nearest point of a closed convex set C to x exactly when Rexp,yp0 for every yC (Variational characterisation of the nearest point).

[A3]

The pairing is linear in the first argument and conjugate-linear in the second, S={v:v,s=0 sS} is a linear subspace, and vSS with v,v=0 forces v=0 (Orthogonality and the orthogonal complement, Real and complex inner-product spaces and their induced length).

[A4]

Countable Choice is the selection principle consumed by the nearest-point theorem (The Axiom of Countable Choice (ACω)).

Proof

technique · direct

Given: Countable Choice, a Hilbert space H, a closed linear subspace MH and a vector xH.

1.1

Since M is a nonempty closed convex set, x has a unique nearest point p in M.

A1A4
2.1

The variational inequality gives Rexp,wp0 for every wM. For uM, take w=p+u and w=pu to obtain Rexp,u=0. Over R the pairing is real-valued, so this already gives xp,u=0. Over C, also iuM, and the same real-part conclusion applied to iu gives 0=Rexp,iu=Re(ixp,u)=Imxp,u. Thus in either scalar field xp,u=0 for every uM, that is xpM.

step 1.1A1A2A3algebra
3.1

Setting m=p and n=xp gives a decomposition x=m+n with mM and nM.

step 2.1A3
4.1

If x=m1+n1=m2+n2 are two such decompositions, then v=m1m2=n2n1 lies in MM, since both M and M are linear subspaces, so v,v=0 and v=0; hence m1=m2, n1=n2, and the decomposition is unique.

step 3.1A3algebra
DefinitionDefinition: AI-adaptedProof: Not applicablejudge pass (gpt-5.6-terra)audited 2026-09-22Open item page →

The Hilbert orthogonal projection onto a closed subspace

Definition

Assume the Axiom of Countable Choice. Let M be a closed linear subspace of a real or complex Hilbert space H (Linear subspace of a vector space). By the orthogonal-decomposition theorem (Orthogonal decomposition by a closed subspace) every xH has a unique representation

x=PMx+(xPMx),PMxM,xPMxM,

and the Hilbert orthogonal projection onto M is the map

PM:HMH,xPMx,

assigning to x its unique M-component. Its defining properties are therefore

PMxM,xPMxM(xH),

which characterise PM uniquely: a map with these defining properties must agree with the M-component of the unique decomposition of each x.

Agreement with the finite-dimensional projection. If V is a finite-dimensional inner-product space and WV a subspace, then For a subspace W of a finite-dimensional inner product space, V=WW writes V=WW and The orthogonal projection PWv is the W-component in V=WW defines PWv as the unique W-component of v; the defining properties displayed above are the same, so they define the same map on a finite-dimensional Hilbert space.

Range and kernel. PMxM for every x, and PMm=m for mM because m=m+0 with 0M; conversely PMx=0 says exactly that x=x0M. Hence the range of PM is M and its kernel is M, and PM is the identity on M and zero on M.

LemmaStatement: AI-adaptedProof: AI-adaptedaudited 2026-09-22Open item page →

Hilbert projections are linear, self-adjoint and contractive

Statement

Assume the Axiom of Countable Choice. Let M be a closed linear subspace of a real or complex Hilbert space H and let PM be the Hilbert orthogonal projection onto M. Then:

  1. PM is linear and idempotent, ranPM=M and kerPM=M;
  2. PMx,y=x,PMy for all x,yH, that is PM is self-adjoint;
  3. PMxx for every x, so PM is a bounded linear operator of norm at most 1; and if M{0}, then PM=1.

Facts & Assumptions

[A1]

PMxM and xPMxM, and a vector in M is orthogonal to every vector of M (The Hilbert orthogonal projection onto a closed subspace, Orthogonality and the orthogonal complement).

[A2]

M and M are linear subspaces, so they are closed under sums and scalar multiples (Linear subspace of a vector space, Orthogonality and the orthogonal complement).

[A3]

For pairwise orthogonal vectors, u+v2=u2+v2 (Pythagoras and finite orthogonal sums).

[A4]

A bounded linear operator has finite operator norm, and T=sup{Tx:x1} with TxTx (A bounded linear operator between normed spaces, The operator norm as the least bound and as the unit-sphere or unit-ball supremum).

[A5]

Countable Choice is the assumption under which the projection is defined (The Axiom of Countable Choice (ACω)).

Proof

technique · direct

Given: Countable Choice, a closed linear subspace M of a Hilbert space H and the projection PM.

1.1

Linearity: for scalars a,b and x,x, the vector aPMx+bPMx lies in M and (ax+bx)(aPMx+bPMx)=a(xPMx)+b(xPMx) lies in M, so by the defining property of PM it equals PM(ax+bx); idempotence follows because PMxM has zero orthogonal component, so PMPMx=PMx.

A1A2A5
2.1

Range and kernel: PMxM always, PMm=m for mM because mm=0M, and PMx=0 exactly when x=x0M; hence ranPM=M and kerPM=M.

step 1.1A1A2
3.1

Self-adjointness: writing y=PMy+(yPMy) and using additivity in the second argument together with yPMyM and PMxM gives PMx,y=PMx,PMy, and symmetrically x,PMy=PMx,PMy; hence the two pairings agree.

step 2.1A1A2
4.1

Contractivity: x=PMx+(xPMx) is a sum of orthogonal vectors, so Pythagoras gives x2=PMx2+xPMx2PMx2, hence PMxx and PM1 by the definition of the operator norm; if M{0} choose 0mM, then PMm=m gives PMPMm/m=1, so PM=1.

step 3.1A3A4algebra
TheoremStatement: AI-adaptedProof: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-22Open item page →

The double orthogonal complement of a subspace is its closure

Statement

Assume the Axiom of Countable Choice. Let M be a linear subspace of a real or complex Hilbert space H. Then

M=M,

where M is the norm closure of M and M=(M).

Facts & Assumptions

[A1]

S is a linear subspace, SS, and ST implies TS (Orthogonality and the orthogonal complement).

[A2]

S is closed for every subset S, and the closure of a set is the smallest closed superset, so M is contained in every closed set containing M. A point lies in M exactly when every norm ball about it meets M (Orthogonal complements are closed, The closure of a nonempty A is {x:d(x,A)=0}, equals A together with its limit points, and is the smallest closed superset).

[A3]

M is a linear subspace and MM={0} (Orthogonality and the orthogonal complement).

[A4]

The inner-product norm is homogeneous and satisfies the triangle inequality (The induced length is a norm).

[A5]

Every closed linear subspace of H splits H as H=NN (Orthogonal decomposition by a closed subspace).

[A6]

Countable Choice is the hypothesis under which the decomposition is available (The Axiom of Countable Choice (ACω)).

Proof

technique · direct

Given: Countable Choice, a Hilbert space H and a linear subspace MH.

1.1

Every mM is orthogonal to every element of M, so MM; since M is closed by [A2], and M is the smallest closed superset of M, we get MM.

A1A2A6
1.2

The closure N=M is a linear subspace. It contains 0M. If u,vN and r>0, choose u,vM with uu<r/2 and vv<r/2; then u+vM and (u+v)(u+v)<r, so every ball about u+v meets M and u+vN. If a=0, then au=0N; if a0, for every r>0 choose uM with uu<r/a, and then auM and auau<r, so auN.

A2A4
2.1

Let xM and decompose x=n+z with nN and zN; then z=xn lies in M because both x and nNM do, while zNM because MN; hence zMM={0}, so z=0 and x=nM.

step 1.1step 1.2A1A3A5
3.1

Therefore MM by step 2.1, and the reverse inclusion is step 1.1, so M=M for every linear subspace M.

step 1.1step 2.1
TheoremStatement: AI-adaptedProof: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-22Open item page →

Riesz representation for Hilbert spaces

Statement

Assume the Axiom of Countable Choice. Let H be a real or complex Hilbert space and let f be a bounded linear functional on H (The dual space X^* of a normed space and its dual norm). Then there is a unique yH with

f(x)=x,yfor every xH,

and f=y, where f is the dual norm (The operator norm as the least bound and as the unit-sphere or unit-ball supremum). Under the first-variable-linear convention the representing vector depends conjugate-linearly and isometrically on f: if fi is represented by yi and a,b are scalars, then af1+bf2 is represented by ay1+by2.

Facts & Assumptions

[A1]

If f is a bounded linear functional then f=supx1f(x) and f(x)fx, and f=0 exactly when f=0 (The operator norm as the least bound and as the unit-sphere or unit-ball supremum, A bounded linear operator between normed spaces).

[A2]

Cauchy–Schwarz gives u,vuv, and the pairing is linear in the first argument and conjugate-linear in the second with v,v=v2 (Cauchy–Schwarz: x,yxy, with equality exactly for dependent pairs, Real and complex inner-product spaces and their induced length).

[A3]

The kernel of a bounded linear functional is either all of H or a proper linear subspace, and the orthogonal complement of a subspace is closed under the decomposition H=NN for closed N (Linear subspace of a vector space, Orthogonal decomposition by a closed subspace).

[A4]

For a subset S, S={v:v,s=0 sS} (Orthogonality and the orthogonal complement).

[A5]

Countable Choice is the hypothesis under which the orthogonal decomposition, and hence this representation, is obtained (The Axiom of Countable Choice (ACω)).

Proof

technique · direct

Given: Countable Choice, a real or complex Hilbert space H and a bounded linear functional f on H.

1.1

If f=0, then y=0 represents f because x,0=0 for every x, and f=0=y; the same f has no other representing vector, since a vector y representing f satisfies y,y=0 and hence y=0.

A1A2
1.2

If f0, its kernel is a proper linear subspace of H: it is linear because f(au+bv)=af(u)+bf(v), it is proper because f takes a nonzero value, and it is closed because xnx and f(xn)=0 give f(x)f(x)f(xn)fxxn0.

A1A3
2.1

Choose z with f(z)0 and put u=z/f(z), so f(u)=1; decompose u=m+n with mkerf and n(kerf), then 1=f(u)=f(m)+f(n)=f(n) shows n0 and f(n)=1.

step 1.2A3A5
3.1

For arbitrary x, the vector v=xf(x)u satisfies f(v)=f(x)f(x)1=0, hence v,n=0 and x,n=f(x)u,n; moreover u,n=m+n,n=m,n+n,n=0+n2, so f(x)=x,n/n2=x,n/n2 with y:=n/n2.

step 2.1A2A4algebra
4.1

Norm and uniqueness: Cauchy–Schwarz gives f(x)=x,yxy, so fy, while f(y)=y2 gives fy; hence f=y, and this contains the case f=0. If also f(x)=x,y for all x, then x,yy=0 for all x, and the choice x=yy gives yy2=0, so y=y.

step 3.1A1A2algebra
5.1

Conjugate linearity: if fi(x)=x,yi for i=1,2, then for all x and scalars a,b one has (af1+bf2)(x)=ax,y1+bx,y2=x,ay1+by2 by conjugate-linearity in the second argument; uniqueness of the representing vector therefore gives the representing vector ay1+by2, so the map fy is conjugate-linear, and by step 4.1 it is isometric.

step 4.1A2algebra
6.1

Steps 1.1, 3.1 and 4.1 produce the unique representing vector together with the norm identity for every bounded f, and step 5.1 records its conjugate-linear isometric dependence; Countable Choice is used exactly through the orthogonal decomposition of step 2.1.

step 1.1step 2.1step 3.1step 4.1step 5.1A5
CorollaryStatement: AI-adaptedProof: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-22Open item page →

Hilbert spaces are reflexive

Statement

Assume the Axiom of Countable Choice. Every real or complex Hilbert space H is reflexive: the canonical evaluation map JH:HH is surjective.

Facts & Assumptions

[A1]

Riesz representation: for every bounded linear functional f on H there is a unique yH with f(x)=x,y for all x, and f=y; writing R(y):=,y defines a bijection R:HH that is conjugate-linear, and linear in the real case (Riesz representation for Hilbert spaces, The dual space X^* of a normed space and its dual norm).

[A2]

The canonical map is (JHx)(f)=f(x) and does not depend on choices (The canonical evaluation map into the bidual).

[A3]

H is reflexive exactly when JH is surjective (Reflexivity is surjectivity of the canonical map).

[A4]

The pairing is conjugate-linear in the second argument, so z,y=y,z (Real and complex inner-product spaces and their induced length).

[A5]

Countable Choice is the hypothesis of the Riesz representation theorem used below (The Axiom of Countable Choice (ACω)).

Proof

technique · direct

Given: Countable Choice, a real or complex Hilbert space H, its dual H, bidual H and canonical map JH.

1.1

By [A1] the Riesz map R:HH is a bijection with R(y)(x)=x,y and R(y)=y.

A1A5
2.1

Let ΦH and define ψ(y)=Φ(R(y)); since R is conjugate-linear and Φ is linear, ψ(ay)=aψ(y) and ψ(y+y)=ψ(y)+ψ(y), while ψ(y)ΦR(y)=Φy; hence φ:=ψ is a linear functional on H with φ(y)Φy.

step 1.1A1
3.1

Applying Riesz representation to φ gives zH with φ(y)=y,z for every y.

step 2.1A1
4.1

Then for every y one has Φ(R(y))=φ(y)=y,z=z,y=R(y)(z)=JH(z)(R(y)) by [A4] and [A2]; since R is onto H, every element of H has the form R(y), so Φ=JH(z) lies in the range of JH.

step 3.1A1A2A4
5.1

Thus JH is surjective and H is reflexive; the only choice assumption is the one inherited from Riesz representation in step 1.1.

step 1.1step 4.1A3A5
DefinitionDefinition: AI-adaptedProof: Not applicablejudge pass (gpt-5.6-terra)audited 2026-09-22Open item page →

The Hilbert-space adjoint of a bounded operator

Definition

Assume the Axiom of Countable Choice. Let H and K be real or complex Hilbert spaces and let TB(H,K) be a bounded linear operator (A bounded linear operator between normed spaces, The spaces (\mathcal B(X,Y)) and (\mathcal B(X)) of bounded linear operators). For fixed yK the map

xTx,yK

is a bounded linear functional on H: it is linear in x because T is linear and the pairing is linear in its first argument, and Tx,yKTxyTxy by Cauchy–Schwarz and the operator-norm inequality (Cauchy–Schwarz: x,yxy, with equality exactly for dependent pairs, The operator norm as the least bound and as the unit-sphere or unit-ball supremum). By Riesz representation (Riesz representation for Hilbert spaces) there is therefore a unique vector TyH with

Tx,yK=x,TyHfor every xH.

The Hilbert adjoint of T is the map

T:KH,yTy.

It is the unique map KH satisfying the displayed identity, since two such maps have x,(T1T2)y=0 for all x and hence (T1T2)y=0 by positive definiteness.

The dictionary with the Banach transpose. Write RH:HH and RK:KK for the Riesz maps RH(x)=,xH and RK(y)=,yK, and let TB(K,H) be the transpose of T, (Tg)(x)=g(Tx) (The transpose of a bounded operator). Then for all yK and xH,

(RH(Ty))(x)=x,TyH=Tx,yK=(RKy)(Tx)=(T(RKy))(x),

so RHT=TRK. The Hilbert adjoint is thus the Banach transpose conjugated by the Riesz identifications of H and K with their duals; it is a different operator from T whenever the Riesz maps are conjugate-linear.

TheoremStatement: AI-adaptedProof: AI-adaptedaudited 2026-09-22Open item page →

Hilbert-adjoint identities

Statement

Assume the Axiom of Countable Choice. Let H,K,L be real or complex Hilbert spaces and let R,SB(H,K) and TB(K,L) be bounded linear operators. Then the Hilbert adjoints satisfy:

  1. (aR+bS)=aR+bS for scalars a,b, and the adjoint of an operator is unique;
  2. (TS)=ST;
  3. T=T and T=T;
  4. TT=T2.

Facts & Assumptions

[A1]

The Hilbert adjoint of TB(K,L) is the unique map T:LK with Tx,yL=x,TyK for all x,y (The Hilbert-space adjoint of a bounded operator).

[A2]

The pairing is linear in the first argument, conjugate-linear in the second, conjugate symmetric, and v,v=0 implies v=0 (Real and complex inner-product spaces and their induced length).

[A3]

The operator norm satisfies TuTu and is the unit-ball supremum (The operator norm as the least bound and as the unit-sphere or unit-ball supremum), while composition obeys UVUV (Composition satisfies |ST|\le|S|,|T|); a linear map is bounded if it admits a finite constant C0 with UyCy for every y (A bounded linear operator between normed spaces).

[A4]

Cauchy–Schwarz gives u,vuv (Cauchy–Schwarz: x,yxy, with equality exactly for dependent pairs).

[A5]

Countable Choice is the hypothesis of the Riesz construction of adjoints (The Axiom of Countable Choice (ACω)).

Proof

technique · direct

Given: Countable Choice, Hilbert spaces H,K,L and bounded operators R,SB(H,K), TB(K,L).

1.1

First let U:XY be any bounded linear operator between Hilbert spaces over the same scalar field. The map U:YX exists by the adjoint construction. For y,zY, scalars a,b and xX, its identity gives x,U(ay+bz)=Ux,ay+bz=ax,Uy+bx,Uz=x,aUy+bUz. Positive definiteness applied to the difference proves that U is linear. Also Uy2=U(Uy),yU(Uy),yUUyy, so division when Uy0, and the trivial inequality otherwise, give UyUy. Thus U is bounded and its now-defined operator norm satisfies UU. This applies to each bounded operator used below, including an adjoint once its boundedness has been established.

A1A2A3A4A5algebra
2.1

For uniqueness of the adjoint and conjugate-linearity in the operator, let U,VB(K,H) both satisfy the defining adjoint identity for the same operator in B(H,K). For yK, one has x,(UV)yH=0 for every xH; taking x=(UV)y gives (UV)y=0. For scalars a,b, the identities (aR+bS)x,yK=aRx,yK+bSx,yK=x,aRy+bSyH hold for all xH and yK, so (aR+bS)=aR+bS.

step 1.1A1A2A5
3.1

Composition and involution: for xH and yL, x,STyH=Sx,TyK=TSx,yL, so (TS)=ST by uniqueness. Likewise, for xK and yL, the defining identity for T gives Ty,xK=y,TxL; conjugate symmetry and the defining identity for T give Tx,yL=x,TyK=Tx,yL, so T=T by uniqueness.

step 1.1step 2.1A1A2
4.1

Norms: Cauchy–Schwarz gives Ty2=Ty,TyK=T(Ty),yLTTyy, hence TyTy (trivially when Ty=0) and TT; applying this to T and using T=T gives T=T. Moreover TTTT=T2, while for x1 one has Tx2=x,TTxKxTTxTT, so T2TT and hence TT=T2.

step 1.1step 3.1A3A4algebra
DefinitionDefinition: AI-adaptedProof: Not applicablejudge pass (gpt-5.6-terra)audited 2026-09-22Open item page →

Self-adjoint, positive, unitary and normal operators

Definition

Assume the Axiom of Countable Choice, and let H be a real or complex Hilbert space with TB(H) a bounded linear operator and T its Hilbert adjoint (The Hilbert-space adjoint of a bounded operator, The spaces (\mathcal B(X,Y)) and (\mathcal B(X)) of bounded linear operators).

  • T is self-adjoint when T=T;
  • T is positive when Tx,x is a real number in [0,+) for every xH;
  • T is unitary when TT=TT=I, the identity operator;
  • T is normal when TT=TT.

The definitions are read over either scalar field with the same inner product. Two immediate consequences. Every self-adjoint operator is normal, because TT=T2=TT when T=T. Every unitary operator is normal, because its defining identity says exactly that TT and TT are both the identity. Positivity is a condition on the values of the quadratic form and therefore forces those values to be real, which for a complex Hilbert space does not follow from boundedness alone; a positive operator on a complex Hilbert space is in fact self-adjoint, but that is proved later and is not assumed here.

Consistency of the vocabulary. The identity operator is self-adjoint, positive and unitary, and the zero operator is self-adjoint and positive; on the one-dimensional Hilbert space C the operator λI is self-adjoint exactly when λ is real, unitary exactly when λ=1, and normal for every scalar λ.

LemmaStatement: AI-adaptedProof: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-22Open item page →

Kernel–range orthogonality for Hilbert adjoints

Statement

Assume the Axiom of Countable Choice. Let TB(H,K) be a bounded linear operator between real or complex Hilbert spaces, with kernel kerT={x:Tx=0}, range ranT=T[H] and Hilbert adjoint TB(K,H). Then

(ranT)=kerT,(ranT)=kerT,

and consequently

ranT=(kerT),ranT=(kerT).

Facts & Assumptions

[A1]

Tx,yK=x,TyH for all xH, yK, and the adjoint is a bounded linear operator (The Hilbert-space adjoint of a bounded operator, A bounded linear operator between normed spaces).

[A2]

T=T (Hilbert-adjoint identities).

[A3]

S={v:v,s=0 sS}; if v,w=0 for every w then v=0, and S=S for every linear subspace S (Orthogonality and the orthogonal complement, Real and complex inner-product spaces and their induced length, The double orthogonal complement of a subspace is its closure).

[A4]

The image of a linear map is a linear subspace, and the kernel of a linear map is a linear subspace (Linear subspace of a vector space).

[A5]

Countable Choice is the hypothesis under which adjoints and double complements are available (The Axiom of Countable Choice (ACω)).

Proof

technique · direct

Given: Countable Choice, Hilbert spaces H,K and a bounded linear operator T:HK.

1.1

For yK, one has y(ranT) exactly when Tx,yK=0 for every x, which by the adjoint identity is exactly when x,TyH=0 for every x; taking x=Ty shows this happens exactly when Ty=0, that is ykerT.

A1A3A5
2.1

Replacing T by T in step 1.1 and using T=T gives (ranT)=kerT.

step 1.1A2
3.1

The range of a linear map is a linear subspace, so the double-complement theorem applies to it: ranT=(ranT)=((ranT))=(kerT), and likewise ranT=(kerT).

step 1.1step 2.1A3A4
RemarkRemark: AI-adaptedProof: Not applicablejudge pass (gpt-5.6-terra)audited 2026-09-22Open item page →

Agreement with the concrete L-two projection

Remark

Assume the Axiom of Choice, and let H be complex L2(μ) or a closed linear subspace of it with MH a closed linear subspace (Closed l two subspaces have orthogonal projections). That published theorem constructs a linear contraction PM:HH with PMfM and fPMfM for every f, together with H=MM.

The Hilbert orthogonal projection of The Hilbert orthogonal projection onto a closed subspace is characterised by the same two properties: its value at f is the unique M-component of the unique orthogonal decomposition f=PMf+(fPMf) with fPMfM. Since the concrete construction supplies a vector of M whose residual is orthogonal to M, and the orthogonal decomposition is unique, the concrete map and the Hilbert projection agree wherever both are defined. The concrete theorem is used only to identify the two constructions: it is not a supplier for the existence, linearity, contractivity or self-adjointness of the Hilbert projection, which are proved on this page from the abstract decomposition.

The choice cost of the identification is the concrete theorem's: it assumes AC, and AC implies the Axiom of Countable Choice, under which the abstract projection exists (The Axiom of Choice). No stronger principle is claimed, and the identification is orientation only, not a load-bearing prerequisite of any theorem on this page.

RemarkRemark: AI-adaptedProof: Not applicablejudge pass (gpt-5.6-terra)audited 2026-09-22Open item page →

Lax–Milgram is owned by the PDE track

Remark

The seam contract of this track assigns the Lax–Milgram theorem and the vocabulary of bounded and coercive sesquilinear forms to the partial-differential-equations development, and this page does not state them. What this page supplies is Riesz representation for Hilbert spaces, which the PDE track may cite, together with the bounded-operator vocabulary of A bounded linear operator between normed spaces: on a real or complex Hilbert space every bounded linear functional is represented by a vector, and that is the ingredient from which a later page proves Lax–Milgram after defining its own forms, boundedness, coercivity and continuity hypotheses.

Nothing on the present page assumes coercivity, symmetry or continuity of a sesquilinear form, and no representation of a form by an operator is asserted. Assuming the Axiom of Countable Choice, the Riesz theorem available here carries that hypothesis, and any later consumer that invokes it inherits the same assumption (The Axiom of Countable Choice (ACω)).

5 · Examples, counterexamples and false statements

None yet.

Sources