IterativeAmplitudeEstimation¶
- class IterativeAmplitudeEstimation(epsilon_target, alpha, confint_method='beta', min_ratio=2, quantum_instance=None)[소스]¶
기반 클래스:
qiskit.algorithms.amplitude_estimators.amplitude_estimator.AmplitudeEstimator
The Iterative Amplitude Estimation algorithm.
This class implements the Iterative Quantum Amplitude Estimation (IQAE) algorithm, proposed in [1]. The output of the algorithm is an estimate that, with at least probability \(1 - \alpha\), differs by epsilon to the target value, where both alpha and epsilon can be specified.
It differs from the original QAE algorithm proposed by Brassard [2] in that it does not rely on Quantum Phase Estimation, but is only based on Grover’s algorithm. IQAE iteratively applies carefully selected Grover iterations to find an estimate for the target amplitude.
참조
- [1]: Grinko, D., Gacon, J., Zoufal, C., & Woerner, S. (2019).
Iterative Quantum Amplitude Estimation. arXiv:1912.05559.
- [2]: Brassard, G., Hoyer, P., Mosca, M., & Tapp, A. (2000).
Quantum Amplitude Amplification and Estimation. arXiv:quant-ph/0005055.
The output of the algorithm is an estimate for the amplitude a, that with at least probability 1 - alpha has an error of epsilon. The number of A operator calls scales linearly in 1/epsilon (up to a logarithmic factor).
- 매개변수
epsilon_target (
float
) – Target precision for estimation target a, has values between 0 and 0.5alpha (
float
) – Confidence level, the target probability is 1 - alpha, has values between 0 and 1confint_method (
str
) – Statistical method used to estimate the confidence intervals in each iteration, can be 〈chernoff〉 for the Chernoff intervals or 〈beta〉 for the Clopper-Pearson intervals (default)min_ratio (
float
) – Minimal q-ratio (\(K_{i+1} / K_i\)) for FindNextKquantum_instance (
Union
[QuantumInstance
,Backend
,BaseBackend
,None
]) – Quantum Instance or Backend
- 예외 발생
AlgorithmError – if the method to compute the confidence intervals is not supported
ValueError – If the target epsilon is not in (0, 0.5]
ValueError – If alpha is not in (0, 1)
ValueError – If confint_method is not supported
Methods
Construct the circuit \(\mathcal{Q}^k \mathcal{A} |0\rangle\).
Run the amplitude estimation algorithm.
Attributes
- epsilon_target¶
Returns the target precision
epsilon_target
of the algorithm.- 반환 형식
float
- 반환
The target precision (which is half the width of the confidence interval).
- quantum_instance¶
Get the quantum instance.
- 반환 형식
Optional
[QuantumInstance
]- 반환
The quantum instance used to run this algorithm.