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 Boolean query problem and error model for adversary bounds
Definition
Fix an integer N≥1, a nonempty finite set D⊆{0,1}^N, and a Boolean function f:D→{0,1}. A Boolean query problem is the tuple (N,D,f) with input x∈D and standard XOR oracle The local address register is with ordered basis , . For its qubit realization, set and encode by the -bit binary word for . Define the total bit function on all -bit words by for and for . The standard bit-flip query for restricts to on the encoded local register and acts as the identity on unused address codewords. Algorithms in the local model use the -address register at query calls.
For 0≤ε<1/2, Q_ε(f) is the least worst-case number of these oracle calls of an algorithm outputting f(x) with probability at least 1−ε for every x∈D. The input promise does not restrict the oracle address. Only query calls are counted here; no gate-efficiency assertion is part of this definition.
Facts & Assumptions
Given: A finite Boolean query problem and its fixed standard XOR query convention.
QA task and promise domain: a finite promise task specifies a domain and a Boolean decision function on that domain.
Standard bit-flip query convention: a total bit function on an ordered bit-string address register defines a unitary, involutive XOR query.
Quantum query complexity: the general query-cost interface counts the worst-case number of designated oracle calls; its bounded-error convention uses the fixed 2/3 success threshold.
Dirac Notation Conversion: computational-basis kets use the stated Dirac pairing.
Proof
The declared finite set D and map f give the promised decision problem. The extension is defined on every -bit address, so [F2] gives its total XOR unitary. The span of the first address basis states is invariant, and identifying its word for with gives exactly the displayed ; unused codewords are fixed because their extension bit is zero. Thus the local oracle is total on its -address register, including when and . The promise restricts x, not which address in may be queried.
The local Q_ε clause in the Definition counts the least worst-case number of designated calls to this oracle among algorithms correct with probability at least 1−ε on every promised input; [F3] supplies the general worst-case query-cost convention and excludes nonoracle gates. Equation (F4)'s ket convention fixes all later matrix and state formulas.
Depends on
Used by
- Bounded-error evaluation from a dual adversary certificate Algorithm
- Controlled input-consistency reflection from a bit query Algorithm
- Input-mismatch masks and entrywise filtering Definition
- Query-address projectors for bit-oracle algorithms Definition
- Dual adversary certificate for OR_N Example
- Adversary progress at initial and bounded-error final states Lemma
- Finite-dimensional well-definedness of the filtered γ₂ program Lemma
- Finite, attained general adversary value for nonconstant Boolean functions Lemma
- The four-bit Ambainis function separates nonnegative and signed adversary bounds Proposition
- Dual reflection evaluator has bounded-error correctness Theorem
- General adversary bound characterizes Boolean quantum query complexity Theorem
- General adversary spectral lower bound for quantum queries Theorem
- Nonnegative and signed adversary bounds compose from below Theorem
- The controlled input-consistency circuit realizes the exact reflection Theorem
Dependency tree · two levels
19 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 (17 April 2025) (standard reference, not scraped)
- Ronald de Wolf, Quantum Computing: Lecture Notes, arXiv:1907.09415v6 (standard reference, not scraped)