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.
is a vector-space isomorphism
Statement
Let be finite-dimensional vector spaces over , with ordered bases and . The map
is a vector-space isomorphism.
Facts & Assumptions
Given: The finite-dimensional spaces and ordered bases in the Statement.
is a vector space under pointwise operations ( is a vector space over the common scalar field).
An ordered basis gives every vector a unique coordinate list (A finite list is an ordered basis if and only if every equals for exactly one ; those scalars are the coordinates of in that ordered basis).
A linear isomorphism is a linear map with a two-sided linear inverse (Invertible linear maps, linear isomorphisms, and inverse linear maps).
Proof
For every basis vector , coordinate uniqueness in [L2] gives and , so is linear column by column.
If , then [L2] gives for every ; linearity and the unique expansion of every vector in give , so is injective.
Given , prescribe and, for the unique expansion from [L2], define . This is well defined and linear, and the -th matrix column is the -th column of ; hence . Together with steps 1.1 and 2.1, is a linear bijection. Its set-theoretic inverse is linear: if and , then injectivity and linearity give and . Thus is a linear isomorphism by [L3].
If , then is the zero space and both sides contain only their zero element; if , then and are zero spaces and the only map is the zero map. Thus the construction also proves the isomorphism in every zero-dimensional case.
Depends on
is a vector space over the common scalar field
Invertible linear maps, linear isomorphisms, and inverse linear maps
Coordinate columns and matrices of linear maps relative to ordered bases
A finite list is an ordered basis if and only if every equals for exactly one ; those scalars are the coordinates of in that ordered basis
The vector space of by matrices over a field, with entrywise operations