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 registers and their ordered computational bases
Definition
For an integer , the -level register is the complex inner-product space with the standard pairing , linear in the first argument as in Real and complex inner-product spaces and their induced length and The standard formulas on and on are inner products. Its computational basis is the ordered standard basis of The standard list with and for is an ordered basis of ; hence , and is the zero space with basis and dimension . The register's alphabet is the ordered set .
For , the -qubit register is the ordered tensor product over of copies of . Here is the algebraic module tensor product (The tensor product from the additive group underlying the free -module on , elementary tensors, and finite tensor sums), with its complex-module structure and finite iterated/empty-product conventions from Over a commutative ring, is an -module with and Finite iterated tensor products represent multilinear maps independently of parenthesization. The tuple of bit positions is ordered lexicographically, with the first wire as the most significant position; the product-basis theorem below establishes the corresponding elementary tensors as a basis. For , the empty tensor product is with basis . This one-dimensional trivial register is distinct from the zero vector space . By definition a register has positive dimension; a zero-dimensional space may still occur as a factor in the more general tensor-space construction below.
Depends on
- Real and complex inner-product spaces and their induced length
- Finite-dimensional vector space, and its dimension $\dim_F V$; infinite-dimensional means having no finite basis
- The vector space $F^{X}$ of all functions $X \to F$ with pointwise operations, and $F^{n}$ as the case $X = n = \{0, 1, \dots, n-1\}$
- The standard list $e : n \to F^{n}$ with $e_i(i) = 1_F$ and $e_i(j) = 0_F$ for $j \ne i$ is an ordered basis of $F^{n}$; hence $\dim_F F^{n} = n$, and $F^{0}$ is the zero space with basis $\varnothing$ and dimension $0$
- The standard formulas $\langle x,y\rangle=\sum_{k<n}x_k y_k$ on $\mathbb R^n$ and $\sum_{k<n}x_k\overline{y_k}$ on $\mathbb C^n$ are inner products
- The tensor product $M\otimes_R N$ from the additive group underlying the free $\mathbb Z$-module on $M\times N$, elementary tensors, and finite tensor sums
- Over a commutative ring, $M\otimes_RN$ is an $R$-module with $r(m\otimes n)=(rm)\otimes n=m\otimes(rn)$
- Finite iterated tensor products represent multilinear maps independently of parenthesization
Used by
- Complete-graph continuous-time search Algorithm
- Controlled input-consistency reflection from a bit query Algorithm
- Costed coherent evaluation of cyclic group powers Algorithm
- Exact Two-Level Elimination of a Unitary Algorithm
- Five-local history-state adiabatic path Algorithm
- HHL finite sine-window phase-estimation algorithm Algorithm
- Hypercube continuous-time state transfer Algorithm
- One finite abelian hidden-subgroup Fourier sample Algorithm
- One-query Bernstein–Vazirani algorithm Algorithm
- One-query Deutsch algorithm Algorithm
- One-query Deutsch–Jozsa algorithm Algorithm
- Power-of-two dihedral hidden-subgroup sieve Algorithm
- Quantum phase estimation Algorithm
- Reversible binary dot-product query Algorithm
- Reversible embedding of a Boolean circuit Algorithm
- Reversible modular multiplication by a unit Algorithm
- Reversible zero-completion of an N-address bit query Algorithm
- Simon promise decision by sampled rank Algorithm
- Simultaneous-message equality by quantum fingerprints Algorithm
- Stabilizer encoder by symplectic elimination Algorithm
- Distance corrects unlocated errors and known erasures Corollary
- A preserved unknown state cannot program its own reflection Counterexample
- Fidelity and trace-distance inequalities do not imply QRE data processing Counterexample
- Generator convention matters Counterexample
- Normalized states can have infinite quantum relative entropy Counterexample
- Abort-aware real and ideal QKD outputs and security errors Definition
- Big-endian encoding of ordered bit strings Definition
- Binary phase-query convention Definition
- Boolean oracle query model for search lower bounds Definition
- Choi matrix with input factor first Definition
- Clean and dirty ancillas Definition
- Clean-ancilla zero-branch postselection Definition
- Code-based quantum fingerprint Definition
- Coherent finite sampler and observable value Definition
- Coherent XOR function oracle Definition
- Completely positive maps Definition
- Continuous-time quantum walk Definition
- CSS code from nested binary codes Definition
- Eigenphase estimation access model Definition
- Finite abelian hidden-subgroup promise and output encoding Definition
…and 118 more results.
Dependency tree · two levels
44 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 (standard reference, not scraped)
- Ronald de Wolf, Quantum Computing: Lecture Notes (standard reference, not scraped)