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.
Expected cost of unknown-amplitude search
Statement
For , the expected total number of calls made by Unknown-amplitude randomized search to , , the good and zero-input phase operations, and any one-call verifier is . The lower bound is for this specified schedule; no general optimality statement is made outside an explicit black-box search model. For , the expected query cost is infinite.
Facts & Assumptions
Given: The round schedule, fresh-register semantics, and access model of the unknown-amplitude procedure.
Unknown-amplitude randomized search: ; each round uses one direct sample and, if it fails, one fresh preparation, uniform , and standard iterates.
Unknown-amplitude search has no false positives and halts almost surely: for uniform , the amplification-attempt success probability is at least ; all returned outputs are good and halts almost surely.
Exact success probability after amplitude amplification: after iterates the good probability is .
Expected query cost from finite execution prefixes: expected query cost is the supremum of expectations over finite execution prefixes; no expectation on an infinite-history space is presumed.
Quantum query complexity and Circuit-family and computation cost model: oracle calls, gates, and classical work are separate resource coordinates.
The addition formulas for complex trigonometric and hyperbolic functions: sine and cosine addition identities; follows from Parity and the Pythagorean identity for sine and cosine.
Proof
For , write . Once , [F2] gives amplification-attempt success at least , so the conditional probability of reaching the next round is at most . If , then and the survival-weighted cost ratio of later rounds is at most .
Let . For every , : it holds directly for , and if it holds for , then . Thus . With , we have , so the first threshold index is at most . If , then and ; the same bound holds when . Before that threshold the grow geometrically, so their sum is ; the direct preparations and fixed-cost verifications also cost . A round that reaches its amplification attempt makes at most four named calls per iterate, at most one extra preparation call, and at most one verifier call for each of its two samples; including the first direct sample, its total is at most . After the threshold, [F1], step 1.1, and make the survival-weighted worst-case round costs contract by at most . Since , the total is . If , each direct sample succeeds with probability at least , and for ; worst-case round costs grow by at most a factor , so survival-weighted costs contract by at most , giving . Each bound applies to every finite prefix, and taking the supremum in [F4] proves the upper bound without an infinite-history expectation.
For a lower bound at small , fix and let be the first round with . For every integer , induction with [F6] gives : the base case is equality, and the addition formula bounds the next value by . Therefore the success probability before round is at most , accounting for the direct sample and for the amplified sample. As proved in step 2.1, ; therefore . For sufficiently small , , , and ; geometric summation gives [given, F1, F3, F6, step 2.1, algebra] Hence the chance of any earlier success is at most , which tends to . For all sufficiently small , round is reached with probability at least .
At round , the direct sample fails with probability at least for sufficiently small . Conditional on its fresh amplification attempt, is uniform on , so [given, F1, F4, step 3.1, algebra] The probability of reaching and entering this attempt is at least , so this round alone contributes total access calls. For bounded away from zero, the first direct sample always makes one -call while is bounded, giving the same aggregate lower bound with a smaller constant.
If , every round executes its direct preparation and the process never halts by [F2]. Finite-prefix expected query counts therefore grow without bound with the number of completed rounds, so their supremum in [F4] is . Gate and classical costs remain separate as required by [F5].
Depends on
- Unknown-amplitude randomized search
- Unknown-amplitude search has no false positives and halts almost surely
- Quantum query algorithm
- Quantum query complexity
- Expected query cost from finite execution prefixes
- Circuit-family and computation cost model
- Exact success probability after amplitude amplification
- Complex sine, cosine, hyperbolic sine, and hyperbolic cosine from the complex exponential
- The addition formulas for complex trigonometric and hyperbolic functions
- Parity and the Pythagorean identity for sine and cosine
- Sine and cosine are $1$-Lipschitz on $\mathbb{R}$
- Pi as twice the smallest positive zero of cosine
- Quarter-turn values and shifts by pi/2 and pi
- The derivatives of sine and cosine are cosine and minus sine
- Cosine has a smallest positive zero, lying strictly between zero and two
- The addition formulas for sine and cosine
Used by
Dependency tree · two levels
68 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)
- Ronald de Wolf, Quantum Computing: Lecture Notes (standard reference, not scraped)
- Andrew M. Childs, Lecture Notes on Quantum Algorithms (standard reference, not scraped)