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 amplification from a supplied success lower bound
Definition
Input a finite-register coherent preparation with good projection , as in Prepared unitary and success subspace for amplitude amplification, and represented rational parameters and . The success promise is . Supply under Inverse Unitary Access, the reflections and under Orthogonal-Projector Reflection and Access Contract, and the controlled versions of all operations used under Controlled Unitary Access. The good/bad instrument is the projective measurement of Finite projective measurements. It may be supplied directly or implemented by preparing an ancillary control in , applying controlled , applying a Hadamard to the control and measuring it, with outcome designated good. These implementations and register initialization have their actual declared costs.
By exact rational comparisons compute the least power of two satisfying , and the least positive integer satisfying . Set . More general exact parameter representations are allowed only when they support these finite comparisons.
For trials , carry out the following instructions, stopping at the first return.
- Prepare on a fresh register and perform the good/bad instrument. On a good outcome, return that register. On a bad outcome, discard it.
- Draw exactly fresh independent unbiased random bits, interpret them as an integer , and prepare on a fresh register. Apply exactly iterates of Amplitude amplification with a fixed integer iteration count, then perform the good/bad instrument. On a good outcome, return that register. On a bad outcome, discard it and proceed to the next trial.
If all trials fail, return an explicit failure symbol. Preparations, bits and instruments are fresh between attempts. A classical-output specialization may additionally measure and verify the returned output, charging this work separately; it does not replace the good/bad projective instrument when a conditional quantum state is requested.
Depends on
Used by
Dependency tree · two levels
29 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
- Gilles Brassard, Peter Høyer, Michele Mosca, and Alain Tapp, Quantum Amplitude Amplification and Estimation (standard reference, not scraped)
- Andris Ambainis, Variable time amplitude amplification and a faster quantum algorithm for solving systems of linear equations (standard reference, not scraped)