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.
The categorical dimension of a vector space is the scalar image of its linear dimension
Example
Let be a field. For finite-dimensional -vector spaces with the canonical pivotal structure, the categorical dimension is the image of the usual linear dimension in .
Facts & Assumptions
Given: A field and a finite-dimensional -vector space .
Categorical dimension is the trace of the chosen pivotal comparison (The dimension of an object relative to a pivotal structure).
The ordinary linear dimension is the size of a basis (Finite-dimensional vector space, and its dimension ; infinite-dimensional means having no finite basis).
Finite-dimensional -vector spaces are rigid with the usual duality (Finite-dimensional vector spaces are rigid).
Verification
Let have basis . With the usual duality from [L3], the canonical pivotal structure has component given by , and is by definition the categorical trace of The dimension of an object relative to a pivotal structure.
Using the same basis-and-dual-basis computation as for categorical trace,
The natural number is the ordinary dimension of by Finite-dimensional vector space, and its dimension ; infinite-dimensional means having no finite basis. Hence the categorical dimension is its scalar image in . In positive characteristic this scalar can differ from as a natural number; for example, a -dimensional space has categorical dimension when .
Depends on
Used by
Nothing in the library uses this result yet.
Dependency tree · two levels
22 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
- P. Etingof, S. Gelaki, D. Nikshych, and V. Ostrik, Tensor Categories, Example 4.7.10 (standard reference, not scraped)