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.
Clean-ancilla zero-branch postselection
Definition
Let be a finite register with distinguished unit computational-basis vector (unit by The computational basis is orthonormal), let be a finite-dimensional complex-inner-product space, and define the isometry by . The product inner product makes an isometry; Finite-dimensional linear isometries satisfy the adjoint identity gives , and An isometric quantum encoding gives an orthogonal code projector makes the orthogonal projection onto its image. On elementary tensors this is by the convention of Tensor products of finitely many linear maps. For a unit vector , define its zero-branch vector , zero-branch weight , and complementary-branch weight . When , the conditional system vector is ; when , no conditional vector is assigned. This definition fixes only the clean-ancilla two-outcome branch rule used on this page; it makes no physical realization claim.
Depends on
- Finite registers and their ordered computational bases
- The computational basis is orthonormal
- An isometric quantum encoding gives an orthogonal code projector
- Ordered tensor registers, their inner product, and wire permutations
- Tensor products of finitely many linear maps
- Dirac Notation Conversion
- The adjoint $T^*:W\to V$ is characterised by $\langle Tv,w\rangle_W=\langle v,T^*w\rangle_V$
- Linear isometries, and orthogonal or unitary operators on finite-dimensional inner product spaces
- Finite-dimensional linear isometries satisfy the adjoint identity
- Every linear map between finite-dimensional inner product spaces has a unique adjoint
Used by
Dependency tree · two levels
37 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
- Andrew M. Childs, Lecture Notes on Quantum Algorithms, Chapter 28 §28.3 (standard reference, not scraped)
- Ronald de Wolf, Quantum Computing: Lecture Notes, §9.3 (standard reference, not scraped)