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.
Quantum code as an isometric encoding and its code projector
Definition
Let be a finite-dimensional complex inner-product space and let be a fixed ordered finite register tensor product with , supplied by the QC register interface. A quantum code is an isometric encoding . Its code subspace is , its logical dimension is , and its physical block length is the number of tensor factors. When each physical factor is a qubit, ; a logical -qubit register has . Require .
Using the root library's adjoint convention, the code projector is . The theorem An isometric quantum encoding gives an orthogonal code projector ↗ proves , , and , including one-dimensional logical spaces and the full-space code.
Remarks
The QC02 suppliers set for , order qubit strings lexicographically with the first wire most significant, and distinguish the empty register from (Finite registers and their ordered computational bases). Ordered tensor registers use the factorwise product pairing, linear in the first argument, and declared wire permutations have inverse permutations (Ordered tensor registers, their inner product, and wire permutations). These are the conventions used here.
Depends on
- 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
- Linear map between vector spaces over the same field
- Finite registers and their ordered computational bases
- Ordered tensor registers, their inner product, and wire permutations
- Real and complex inner-product spaces and their induced length
Used by
- Distance corrects unlocated errors and known erasures Corollary
- Detectable operators and distance of a finite-register quantum code Definition
- Exact correction of a protected subsystem Definition
- Exact recovery of an encoded quantum code Definition
- Stabilizer code space Definition
- Support and weight of an operator on a finite register Definition
- A degenerate code with a non-diagonal Knill–Laflamme matrix Example
- Orthogonal error spaces and a recovery branch Example
- Quantum repetition subspace projector and a distance-one boundary error Example
- A unitary error-basis change gives orthogonal error ranges Lemma
- Detectable operators form a subspace and quantum distance is well defined Lemma
- The Knill–Laflamme coefficient matrix is positive Lemma
- An explicit syndrome recovery corrects a Knill–Laflamme error family Theorem
- An isometric quantum encoding gives an orthogonal code projector Theorem
- CSS syndrome correction Theorem
- Exact recovery implies the Knill–Laflamme condition Theorem
- The Knill–Laflamme criterion for a protected subsystem Theorem
Dependency tree · two levels
21 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
- Richard Cleve, Quantum Information Processing course notes, §§36.1, 36.3, and 37.3 (standard reference, not scraped)
- John Preskill, Quantum Computation, Chapter 7, §§7.1 and 7.4.1 (standard reference, not scraped)