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.
Continuous dual of a weak topology
Statement
For a real or complex normed space , the scalar-linear continuous dual of is precisely . No choice principle is required.
Facts & Assumptions
Finite coordinate disks form a weak zero-neighborhood base (Basic weak neighborhoods).
A scalar-linear map on a finite-dimensional normed space is bounded (A linear map from a finite-dimensional normed space is bounded).
Proof
Given: a weakly continuous scalar-linear .
Continuity at zero supplies and such that whenever . If every , every scalar multiple is in this neighborhood. Then for all positive real , forcing . For an empty list this already gives .
Define by . Step 1.1 makes a well-defined scalar-linear functional on . Choose a basis of this subspace and extend it to a basis of by successively adding standard basis vectors when necessary; at most additions occur. Assign value zero on the added basis vectors. The resulting linear extension has the form , where . Only finite-dimensional basis choices occur.
By finite-dimensional boundedness is bounded for the inherited norm, so factorization already gives norm boundedness of . More explicitly and , hence . Conversely, for any and any scalar disk around , its inverse image is a basic weak neighborhood, so is weakly continuous. Thus both inclusions hold.
Depends on
Used by
Dependency tree · two levels
7 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.
Sources
- Bühler–Salamon, Functional Analysis (2017); exact harvest in batch coverage (standard reference, not scraped)
- Teschl, Topics in Real and Functional Analysis (2017); exact harvest in batch coverage (standard reference, not scraped)