Alphabeta Math
TheoremStatement: AI-adaptedProof: AI-adaptedPipeline-generatedaudited 2026-09-22
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Bounded borel pvm integral

Statement

Assume Countable Choice. Let (X,Σ) be a measurable space, let H be a nonzero complex Hilbert space, let E be a projection valued measure on (X,Σ), and let f:X→C be bounded and Σ-measurable (A measurable function between measurable spaces). Then:

  1. there is a unique operator ΦE(f)∈B(H) with ⟨ΦE(f)x,y⟩=∫f dEx,y(x,y∈H), and for every sequence (sn) of complex simple functions with ∥f−sn∥∞→0 one has ∥ΦE(f)−∫sn dE∥→0: the integral is obtained from uniform simple approximations and is independent of the approximating sequence;
  2. ∥ΦE(f)∥≤∥f∥∞, and for every x∈H ⟨ΦE(f)x,x⟩=∫f dEx,∥ΦE(f)x∥2=∫∣f∣2 dEx;
  3. the exact norm is the E-essential supremum ∥f∥E,∞:=sup⁡{∥f∥∞,Ex: x∈H, ∥x∥=1},∥ΦE(f)∥=∥f∥E,∞, where ∥f∥∞,Ex denotes the essential supremum of the real measurable function ∣f∣ with respect to the finite measure Ex (The essential supremum of a measurable function with respect to a measure).

Facts & Assumptions

[A1]

For a complex simple function s the operator ∫s dE satisfies ⟨(∫s dE)x,y⟩=∫s dEx,y, ∥(∫s dE)x∥2=∫∣s∣2 dEx and ∥∫s dE∥≤max⁡∣s∣≤∥s∥∞; the construction is linear on simple functions presented over a common refinement (Simple pvm integral is representation independent).

[A2]

Ex,y is a finite complex measure on (X,Σ) with ∣Ex,y∣(X)≤∥x∥ ∥y∥, the integral ∫g dEx,y of a bounded measurable g satisfies ∣∫g dEx,y∣≤∥g∥∞∣Ex,y∣(X) (Scalar and complex measures from a pvm, Integrals against signed or complex measures are bounded by total variation, Integration against a signed or complex measure, and the class L^1(nu) = L^1(|nu|)).

[A3]

Ex(B)=⟨E(B)x,x⟩=∥E(B)x∥2 is a positive measure with Ex(X)=∥x∥2. Moreover, if E(A)y=y, then E(X∖A)y=E(X∖A)E(A)y=E(∅)y=0, so Ey(X∖A)=0 (Scalar and complex measures from a pvm, Projection valued measure).

[A4]

B(H) is complete for the operator norm (If (Y) is Banach then (\mathcal B(X,Y)) is Banach, Hilbert space).

[A5]

A bounded measurable complex function is integrable against every finite measure and dominated convergence holds: if gn→g pointwise and ∣gn∣≤C with C integrable, then ∫gn dμ→∫g dμ (Dominated convergence).

[A6]

For a finite measure μ, ∥g∥∞,μ is the least essential bound of ∣g∣: ∣g∣≤∥g∥∞,μ μ-almost everywhere, and if ∣g∣≤M almost everywhere then ∥g∥∞,μ≤M; if ∥g∥∞,μ>c then μ({∣g∣>c})>0 (The essential supremum is attained as the least essential bound, The essential supremum of a measurable function with respect to a measure).

[A7]

A complex simple function is a finite linear combination of indicators of pairwise disjoint measurable sets; for a measurable f and ε>0 the square [−M,M]2 containing the range of a bounded f can be cut into finitely many Borel squares of diameter <ε whose inverse images refine to a disjoint measurable cover of X (Complex simple functions as finite sums of measurable indicators, A measurable function between measurable spaces).

[A8]

Countable Choice is the declared standing hypothesis of this block of the page (The Axiom of Countable Choice (ACω)).

Proof

technique · direct

Given: A measurable space (X,Σ), a nonzero complex Hilbert space H, a projection valued measure E on (X,Σ), and a bounded measurable f:X→C with M:=∥f∥∞<+∞.

1.1A7

Uniform simple approximation: for each n≥0 choose finitely many pairwise disjoint measurable sets D1,…,Dr covering X and complex numbers ci with ∣f−ci∣≤1/(n+1) on Di (cut a square containing the range of f into finitely many squares of diameter <1/(n+1) and take inverse images), so sn:=∑ici1Di is a complex simple function with ∥f−sn∥∞≤1/(n+1).

1.2A1

Difference of simple integrals: if s,t are complex simple functions, presenting both over the common refinement of their disjoint normal forms gives ∫(s−t) dE=∫s dE−∫t dE, hence ∥∫s dE−∫t dE∥≤∥s−t∥∞; in particular the sequence ∫sn dE is Cauchy, since ∥∫sn dE−∫sm dE∥≤∥sn−sm∥∞≤1n+1+1m+1.

2.1step 1.2A4

By completeness of B(H) the sequence ∫sn dE has a norm limit ΦE(f), and for any other uniformly approximating sequence (tn) one has ∥∫sn dE−∫tn dE∥≤∥sn−tn∥∞→0, so the limit does not depend on the sequence; the same argument applies to the difference of two candidate limits.

3.1step 2.1A1A2

Pairing identity: for all x,y∈H, ⟨ΦE(f)x,y⟩=lim⁡n⟨(∫sn dE)x,y⟩=lim⁡n∫sn dEx,y=∫f dEx,y, because ∣∫(sn−f) dEx,y∣≤∥sn−f∥∞∣Ex,y∣(X)≤1n+1∥x∥ ∥y∥→0.

4.1step 1.1step 2.1step 3.1A1A3A5

Norm identities: ∥ΦE(f)x∥2=lim⁡n∥(∫sn dE)x∥2=lim⁡n∫∣sn∣2 dEx=∫∣f∣2 dEx by dominated convergence applied to the finite measure Ex with the constant dominating function (M+1)2, since sn→f and ∣sn∣≤M+1; taking y=x in the pairing identity gives ⟨ΦE(f)x,x⟩=∫f dEx.

4.2step 3.1A2

Norm bound and uniqueness: ∣⟨ΦE(f)x,y⟩∣≤∥f∥∞∥x∥ ∥y∥ by the pairing identity just proved and the variation bound, so ∥ΦE(f)∥≤∥f∥∞; and any operator T with ⟨Tx,y⟩=∫f dEx,y for all x,y equals ΦE(f), since T−ΦE(f) has all pairings zero, whence (T−ΦE(f))x=0 for every x by positive definiteness of the pairing.

5.1step 4.1A3A6

Upper bound for the norm: for x≠0 one has Ex=∥x∥2Ex/∥x∥ and hence ∥f∥∞,Ex=∥f∥∞,Ex/∥x∥, so ∥ΦE(f)x∥2=∫∣f∣2 dEx≤∥f∥∞,Ex2∥x∥2≤∥f∥E,∞2∥x∥2 by the least-essential-bound property; therefore ∥ΦE(f)∥≤∥f∥E,∞.

5.2step 4.1A3A6

Lower bound for the norm: write a=∥f∥E,∞. If a=0, the lower bound follows from nonnegativity of the operator norm. If a>0, given 0≤c<a choose a unit vector x with ∥f∥∞,Ex>c, so A:={∣f∣>c} satisfies Ex(A)>0 by the least-essential-bound property; put y:=E(A)x≠0, so Ey(X∖A)=0 and hence ∥ΦE(f)y∥2=∫∣f∣2 dEy≥c2Ey(X)=c2∥y∥2, giving ∥ΦE(f)∥≥c; since 0≤c<a was arbitrary, ∥ΦE(f)∥≥∥f∥E,∞.

6.1step 2.1step 3.1step 4.1step 4.2step 5.1step 5.2A8∎

The integral ΦE(f) is well defined, obtained from uniform simple approximations, satisfies the pairing and quadratic identities and the bound ∥ΦE(f)∥≤∥f∥∞, and its exact norm is the E-essential supremum ∥f∥E,∞.

Depends on

Dependency tree · 2 levels

Sources