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.
Finite ancilla amplification is a well-defined block map
Statement
Let be finite-dimensional complex-inner-product spaces, let , and let have its standard ordered orthonormal basis . For every there is a unique family such that
For every complex-linear , there is a unique operator satisfying
Thus the block rule defines a well-defined linear map on the full operator space. At , it is under the canonical unitary identifications and .
Facts & Assumptions
Given: Finite-dimensional complex-inner-product spaces , an integer , the standard basis of , and a complex-linear map .
Finite registers and their ordered computational bases: the -level register is with ordered standard basis .
Ordered tensor registers, their inner product, and wire permutations: after specifying ordered orthonormal bases for the factors, their tensor register has the product inner product, linear in the first argument.
The product basis is orthonormal and tensor dimensions multiply: product vectors from specified orthonormal bases of the factors form an orthonormal basis of the tensor space.
The space of linear maps with pointwise addition and scalar multiplication: and are the spaces of complex-linear endomorphisms, with pointwise operations.
is a vector space over the common scalar field: pointwise operations make each finite-dimensional linear-map space a complex vector space.
Linear map between vector spaces over the same field: a complex-linear map preserves finite linear combinations.
Finite-dimensional vector space, and its dimension ; infinite-dimensional means having no finite basis: finite-dimensional means having a finite basis; the stated finite-dimensional spaces therefore admit finite bases.
Finite iterated tensor products represent multilinear maps independently of parenthesization: tensor products represent finite multilinear maps, and the scalar space is the tensor unit with its canonical unit identifications.
Gram–Schmidt turns every finite independent list into an orthonormal list with the same successive spans: Gram–Schmidt turns any finite linearly independent list, in particular a basis, into an orthonormal list with the same successive spans.
Proof
Choose finite bases of and , which exist by [F7] and are linearly independent by the basis definition; apply [F9] to obtain orthonormal bases and with the same spans. By [F1]–[F3], and are orthonormal bases of and . For each , uniquely expand . Define and extend linearly from the basis of . Linearity of gives the required block formula on every . Any other family satisfying it has the same coefficients on every product-basis vector, hence each block agrees on the basis and is equal.
On each product-basis vector , prescribe the image . Since these product vectors are a basis, there exists a unique linear operator on with those values. By linearity this gives the displayed rule for all . Define . Uniqueness of the blocks from step 1.1 and uniqueness of an operator from its values on a basis show that this definition is unambiguous.
For , their block families are respectively and . The defining action on the product basis shows that the blocks of are for any scalars . Applying the linearity of from [F6] gives blocks , which are exactly the blocks of . Equality on a basis yields . When , identify with the tensor unit by , and define and by and . These are the corresponding canonical unit identifications of [F8]. By [F3], they send the orthonormal bases chosen in step 1.1 to the corresponding product bases, and [F1]–[F2] show they preserve inner products; hence they are unitary. The sole block equations are and , so and . This is the original map under these identifications.
Depends on
- Finite registers and their ordered computational bases
- Ordered tensor registers, their inner product, and wire permutations
- The product basis is orthonormal and tensor dimensions multiply
- Gram–Schmidt turns every finite independent list into an orthonormal list with the same successive spans
- Finite-dimensional vector space, and its dimension $\dim_F V$; infinite-dimensional means having no finite basis
- Real and complex inner-product spaces and their induced length
- Linear map between vector spaces over the same field
- The space $\mathcal L(V,W)$ of linear maps with pointwise addition and scalar multiplication
- $\mathcal L(V,W)$ is a vector space over the common scalar field
- Finite iterated tensor products represent multilinear maps independently of parenthesization
Used by
Dependency tree · two levels
39 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
- John Watrous, The Theory of Quantum Information (2018), §2.2.1 (standard reference, not scraped)
- John Preskill, Quantum Computation, Chapter 3: Foundations II: Measurement and Evolution, §3.2.6 (standard reference, not scraped)