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Weighted coefficient spaces form a Hilbert scale
Statement
Assume countable choice. Let be a separable real Hilbert space with a complete orthonormal basis indexed by the disjoint union of a finite set and the level indices with and . Write the basis vectors as and . For , define with inner product given by the corresponding weighted coefficient sum and norm squared Then is a separable real Hilbert space. Its displayed basis is complete and orthogonal in , with squared basis norms on the finite family and on level , and the inclusion is continuous with operator norm at most .
Statement references
countable choice, used by the cited countable-basis expansion results
a Hilbert space is complete for its induced norm
separability means an at most countable dense subset
an orthonormal basis has dense linear span and its coefficients determine vectors
the square-summable coefficient norm
real square-summable sequences form a Hilbert space
square-summable coefficients reconstruct a vector from an orthonormal family
Parseval's identity under countable choice
Facts & Assumptions
Given: Countable choice, , its finite orthonormal family and level-indexed orthonormal families, and .
Countable choice is the principle that every countable family of nonempty sets has a choice function. The Axiom of Countable Choice ()
Under countable choice, a complete orthonormal family satisfies Parseval's identity: the sum of squared coefficients of each vector equals its squared norm. Parseval equivalences for an orthonormal family
Real square-summable sequences with their canonical inner product are complete and hence Hilbert. The real square-summable sequence space is complete
Under countable choice, square-summable coefficients on an orthonormal family give a norm-convergent sum whose limit has those coefficients and the corresponding squared norm. Square-summable orthogonal families have norm-convergent finite sums
A topological space is separable when it has an at most countable dense subset. Separability: the existence of an at most countable dense subset
Proof
Given: Countable choice, , , and as in the Statement.
Write and enumerate the basis by placing the finite family first, followed by at index , since is the number of level indices below . For , define by for the finite coordinates and . Parseval [F1] gives , so is an isometry into real .
Given , set the finite-family coefficients equal to its first coordinates and put . Since , the sum of squares of all these coefficients is at most . By [F3], their orthonormal expansion converges in to a vector with those coefficients. Thus and , so is onto. By [F2], the isometric pullback of the real inner product makes complete, and hence a real Hilbert space.
The finite-support rational sequences form a countable subset of real : each is encoded by a finite list of coordinate indices, integer numerators, and positive denominators, and such finite integer lists have an explicit natural-number encoding. Given and , choose so that , then choose rationals with for each , and set for . Then , so these finite-support rational sequences are dense. Because is an isometric bijection by steps 1.1 and 2.1, their inverse images are a countable dense subset of . Hence is separable by [F4].
Each basis vector has a single nonzero coefficient, so its squared norm is on and on level ; distinct basis vectors are orthogonal under the weighted inner product. The finite-support coefficient vectors are dense by step 3.1, so the orthogonal family is complete in . Finally Parseval [F1] gives for , because . Thus the inclusion has operator norm at most .
Depends on
- The Axiom of Countable Choice ($\mathrm{AC}_\omega$)
- Hilbert space
- Separability: the existence of an at most countable dense subset
- Orthonormal families, complete orthonormal systems and Hilbert bases
- Square-summable families on an arbitrary index set and the space $\ell^2(I)$
- The real square-summable sequence space is complete
- Square-summable orthogonal families have norm-convergent finite sums
- Parseval equivalences for an orthonormal family
Used by
Dependency tree · two levels
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Sources
- E. Giné and R. Nickl, Mathematical Foundations of Infinite-Dimensional Statistical Models (Cambridge University Press, 2016) (standard reference, not scraped)
- M. Dashti and A. M. Stuart, The Bayesian Approach to Inverse Problems (arXiv:1302.6989) (standard reference, not scraped)