IterativeAmplitudeEstimation

class qiskit.algorithms.IterativeAmplitudeEstimation(epsilon_target, alpha, confint_method='beta', min_ratio=2, quantum_instance=None, sampler=None)

Bases: AmplitudeEstimator

The Iterative Amplitude Estimation algorithm.

1 - \alpha

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.

References

[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).

Deprecated since version 0.24.0

qiskit.algorithms.amplitude_estimators.iae.IterativeAmplitudeEstimation.__init__() ’s argument quantum_instance is deprecated as of qiskit-terra 0.24.0. It will be removed no earlier than 3 months after the release date. Instead, use the sampler argument. See https://qisk.it/algo_migration for a migration guide.

Parameters

epsilon_target (float) – Target precision for estimation target a, has values between 0 and 0.5
alpha (float) – Confidence level, the target probability is 1 - alpha, has values between 0 and 1
confint_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 FindNextK
quantum_instance (QuantumInstance |Backend | None) – Deprecated: Quantum Instance or Backend
sampler (BaseSampler | None) – A sampler primitive to evaluate the circuits.

Raises

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

Attributes

Returns the target precision epsilon_target of the algorithm.

Returns

The target precision (which is half the width of the confidence interval).

Deprecated. Get the quantum instance.

Deprecated since version 0.24.0

The property qiskit.algorithms.amplitude_estimators.iae.IterativeAmplitudeEstimation.quantum_instance is deprecated as of qiskit-terra 0.24.0. It will be removed no earlier than 3 months after the release date. See https://qisk.it/algo_migration for a migration guide.

Returns

The quantum instance used to run this algorithm.

Get the sampler primitive.

Returns

The sampler primitive to evaluate the circuits.

construct_circuit(estimation_problem, k=0, measurement=False)

\mathcal{Q}^k \mathcal{A} |0\rangle

The A operator is the unitary specifying the QAE problem and Q the associated Grover operator.

Parameters

estimation_problem (EstimationProblem) – The estimation problem for which to construct the QAE circuit.
k (int) – The power of the Q operator.
measurement (bool) – Boolean flag to indicate if measurements should be included in the circuits.

Returns

\mathcal{Q}^k \mathcal{A} |0\rangle

Return type

QuantumCircuit

estimate(estimation_problem)

Run the amplitude estimation algorithm on provided estimation problem.

Parameters

estimation_problem (EstimationProblem) - The estimation problem.

Returns

An amplitude estimation results object.

Raises

Return type

IterativeAmplitudeEstimationResult

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