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.
Deutsch, Deutsch–Jozsa and Bernstein–Vazirani examples
Example
Take all four one-bit Deutsch truth tables. For the two-bit examples use address order and the first bit as the most significant bit. In both the Deutsch–Jozsa and Bernstein–Vazirani example, choose , equivalently secret for Bernstein–Vazirani.
Facts & Assumptions
Given: The finite instances and promise conventions stated by the labelled supplier items below.
Deutsch constant-versus-balanced promise: are constant and are balanced truth tables.
Deutsch–Jozsa promise: a two-bit balanced function has two zero replies and two one replies.
Deutsch algorithm is exact, Deutsch–Jozsa algorithm is exact, and Bernstein–Vazirani algorithm returns the secret exactly: the three quantum procedures have the exact outputs proved on the A page.
Hadamard character sum on F_2^n: for two-bit strings, .
Verification
The Deutsch truth tables give The exact Deutsch theorem [F4] therefore outputs on the first two tables and on the latter two.
For the two-bit Deutsch–Jozsa function , the table is , , , , so it is balanced by [F2]. Its final address amplitude is For , these sums are respectively , so the measured output is . The classical exact bound is queries, and the three-distinct-sample experiment is exact for because any three of four addresses include both output values.
For , the two-bit Bernstein–Vazirani amplitude at is The sums for are , respectively; hence the exact output is . By [F5], classical bounded-error recovery needs at least two queries and the two basis queries suffice.
For Deutsch, the deterministic exact classical query count is two while one randomized query has worst-case success at most by [F5]. For two-bit Deutsch–Jozsa the exact deterministic count is three, while the without-replacement three-sample experiment succeeds with probability one on this finite domain. The finite fair-bit algorithm with replacement has success at least by [F5]. For two-bit Bernstein–Vazirani two classical queries recover both secret bits. These are query counts; none is a classical bit-time claim.
Depends on
- One-query Bernstein–Vazirani algorithm
- One-query Deutsch–Jozsa algorithm
- One-query Deutsch algorithm
- Bernstein–Vazirani no-offset promise
- Binary dot product as parity
- Deutsch–Jozsa promise
- Deutsch constant-versus-balanced promise
- Hadamard character sum on F_2^n
- Classical Bernstein–Vazirani needs n queries for bounded error
- Bernstein–Vazirani algorithm returns the secret exactly
- One classical query cannot solve Deutsch exactly
- Exact deterministic Deutsch–Jozsa needs N/2+1 queries
- Deutsch–Jozsa algorithm is exact
- Three classical samples solve Deutsch–Jozsa with bounded error
- Deutsch algorithm is exact
Used by
Nothing in the library uses this result yet.
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
- Ronald de Wolf, Quantum Computing: Lecture Notes, arXiv:1907.09415v6 (2026-08-27) (standard reference, not scraped)
- John Preskill, Quantum Information, Chapter 6: Quantum Algorithms (updated November 2020) (standard reference, not scraped)