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 free-word formulation implies the canonical-map formulation
Statement
In the one-generator word formalism, the free-word theorem implies the canonical-map form of coherence: the unique arrow of between two binary words of the same length is carried by evaluation to the unique canonical comparison map between the corresponding parenthesised tensor powers of the chosen object.
Facts & Assumptions
Given: Two binary words of the same length and an object of a monoidal category.
In the binary-word category , there is exactly one morphism between two words of the same length (The category of binary words).
Recursive evaluation at defines a strong monoidal functor , and on the unique arrow between equal-length words it uses the canonical comparison isomorphism between the corresponding parenthesised tensor powers of (The word category is the free monoidal category on one generator).
Proof
Because and have the same length, [L1] gives a unique arrow in .
By [L2], the image is exactly the canonical comparison isomorphism between the two parenthesised tensor powers represented by and .
Therefore the unique formal arrow of between and is carried by evaluation to the canonical comparison map between the corresponding tensor powers of . This is precisely the canonical-map formulation in the one-generator setting.
Thus the free-word presentation recovers the canonical-map presentation of coherence for tensor powers of one chosen object.
Depends on
Used by
Nothing in the library uses this result yet.
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
- S. Mac Lane, Categories for the Working Mathematician, Chapter VII.2 (standard reference, not scraped)