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Explicit median confidence guarantee for amplitude estimation
Statement
For rational and , the median procedure of Median confidence amplification for amplitude estimation returns with with probability at least .
Both rational scheduling loops terminate at their least prescribed values, and the odd finite list has a well-defined exact algebraic middle order statistic. Its phase-register size is admissible for the one-run estimator; preparations, queries and comparison bit work retain their separately declared costs.
Facts & Assumptions
Given: The median algorithm, its rational , and the one-run amplitude estimator.
The median algorithm uses and odd with (Median confidence amplification for amplitude estimation).
A one-run estimate has error at most with probability at least (Amplitude-estimation additive error and success probability).
Independent Bernoulli variables satisfy for trials (Chernoff bound for independent bernoulli trials).
The natural logarithm is strictly increasing, satisfies and for positive inputs, and is inverse to the exponential (Order, continuity, range, and the product, quotient, and reciprocal laws for the natural logarithm, The natural logarithm as the inverse of the exponential function).
The one-run QFT estimator has the finite output and access instructions stated in QFT-based amplitude estimation.
Exact rational comparisons and output processing are charged as classical bit operations (Classical bit-operation cost).
Independent repetitions mean separately prepared and measured runs in the quantum query model (Quantum query algorithm).
Exact comparisons of real cyclotomic values terminate (Finite exact comparison of real cyclotomic values).
The real field is Archimedean, natural powers obey , and induction holds on the naturals (Every complete ordered field is Archimedean, Exponentiation of natural numbers, , and its agreement with the integer power in , The principle of mathematical induction).
Proof
The threshold is rational and exceeds by [F22]. By [F26], powers of two are unbounded: choose a natural above any fixed real threshold by the Archimedean property and use induction to get . Thus the doubling loop for terminates, and its first value above the threshold is the least such power; since and , this value is at least , so it is an admissible phase-register size and satisfies the one-run precision requirement. The rational target is finite. Choose a natural by [F26]; if is odd take , and if is even take . Then is positive odd and , so the odd-increment loop for terminates at the least positive odd solution. Each comparison is exact rational arithmetic after clearing denominators.
Each run returns an algebraic estimate in the same real cyclotomic field . Exact finite comparisons determine the middle order statistic; repetitions use independent fresh preparations and readouts by [F24].
From [F1]–[F2] and , a good run has error at most . Its success probability is at least , so each failure indicator has mean at most .
The output is one of the finite run estimates, and the odd sample size makes its middle index unique. Thus the procedure is defined for all stated rational inputs, with query and classical comparison costs remaining separate under [F23].
If the median lies outside , at least runs are failures. For their sum , this entails . Applying the two-sided additive bound [F3] to this containing event gives probability at most .
Here and , so . By [F6], monotonicity and the logarithm product law turn into . Put . By [F5], , so and hence . The reciprocal law in [F6] gives , while the inverse identity gives . Strict increase of therefore implies . Step 2.2 bounds median failure by this quantity, proving success at least .
Depends on
- Median confidence amplification for amplitude estimation
- Amplitude-estimation additive error and success probability
- Chernoff bound for independent bernoulli trials
- Rational bounds for pi used in finite schedules
- The natural logarithm as the inverse of the exponential function
- The natural logarithm has derivative 1/x and equals the integral from 1 to x of 1/t
- Order, continuity, range, and the product, quotient, and reciprocal laws for the natural logarithm
- The mean value theorem, as the case $g(x) = x$ of Cauchy's: for $f$ continuous on $[a,b]$ with $a < b$ and differentiable on $(a,b)$ there is $c \in (a,b)$ with $f(b) - f(a) = f'(c)(b-a)$
- QFT-based amplitude estimation
- Classical bit-operation cost
- Finite exact comparison of real cyclotomic values
- Quantum query algorithm
- Exponentiation of natural numbers, $m^{n}$, and its agreement with the integer power in $\mathbb{R}$
- The principle of mathematical induction
- Every complete ordered field is Archimedean
Used by
- Amplitude-estimation expectation estimator Algorithm
- Median amplitude-estimation query cost Theorem
- Quantum bounded-expectation guarantee and query cost Theorem
Cited to discharge well-definedness by Median confidence amplification for amplitude estimation.
Dependency tree · two levels
102 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
- Brassard, Høyer, Mosca, and Tapp, Quantum Amplitude Amplification and Estimation, complete article, §§4–5, Theorems 11–18 (standard reference, not scraped)
- Andrew M. Childs, Lecture Notes on Quantum Algorithms, complete lecture notes, §§19.1–19.3 (standard reference, not scraped)
- Ronald de Wolf, Quantum Computing: Lecture Notes, complete 239-page notes, §7.3 (standard reference, not scraped)