100 lines
3.7 KiB
Plaintext
100 lines
3.7 KiB
Plaintext
---
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title: FasterAmplitudeEstimation
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description: API reference for qiskit.algorithms.FasterAmplitudeEstimation
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in_page_toc_min_heading_level: 1
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python_api_type: class
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python_api_name: qiskit.algorithms.FasterAmplitudeEstimation
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---
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# FasterAmplitudeEstimation
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<Class id="qiskit.algorithms.FasterAmplitudeEstimation" isDedicatedPage={true} github="https://github.com/qiskit/qiskit/tree/stable/0.20/qiskit/algorithms/amplitude_estimators/fae.py" signature="FasterAmplitudeEstimation(delta, maxiter, rescale=True, quantum_instance=None)" modifiers="class">
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Bases: `qiskit.algorithms.amplitude_estimators.amplitude_estimator.AmplitudeEstimator`
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The Faster Amplitude Estimation algorithm.
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The Faster Amplitude Estimation (FAE) \[1] algorithm is a variant of Quantum Amplitude Estimation (QAE), where the Quantum Phase Estimation (QPE) by an iterative Grover search, similar to \[2].
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Due to the iterative version of the QPE, this algorithm does not require any additional qubits, as the originally proposed QAE \[3] and thus the resulting circuits are less complex.
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**References**
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**\[1]: K. Nakaji. Faster Amplitude Estimation, 2020;**
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[arXiv:2002.02417](https://arxiv.org/pdf/2003.02417.pdf)
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**\[2]: D. Grinko et al. Iterative Amplitude Estimation, 2019;**
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[arXiv:1912.05559](http://arxiv.org/abs/1912.05559)
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**\[3]: G. Brassard et al. Quantum Amplitude Amplification and Estimation, 2000;**
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[arXiv:quant-ph/0005055](http://arxiv.org/abs/quant-ph/0005055)
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**Parameters**
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* **delta** (`float`) – The probability that the true value is outside of the final confidence interval.
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* **maxiter** (`int`) – The number of iterations, the maximal power of Q is 2 \*\* (maxiter - 1).
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* **rescale** (`bool`) – Whether to rescale the problem passed to estimate.
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* **quantum\_instance** (`Union`\[`QuantumInstance`, `Backend`, `BaseBackend`, `None`]) – The quantum instance or backend to run the circuits.
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<Admonition title="Note" type="note">
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This algorithm overwrites the number of shots set in the `quantum_instance` argument, but will reset them to the initial number after running.
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</Admonition>
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## Methods
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### construct\_circuit
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<Function id="qiskit.algorithms.FasterAmplitudeEstimation.construct_circuit" signature="FasterAmplitudeEstimation.construct_circuit(estimation_problem, k, measurement=False)">
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Construct the circuit $Q^k X |0\rangle>$.
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The A operator is the unitary specifying the QAE problem and Q the associated Grover operator.
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**Parameters**
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* **estimation\_problem** (`EstimationProblem`) – The estimation problem for which to construct the circuit.
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* **k** (`int`) – The power of the Q operator.
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* **measurement** (`bool`) – Boolean flag to indicate if measurements should be included in the circuits.
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**Return type**
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`Union`\[`QuantumCircuit`, `Tuple`\[`QuantumCircuit`, `List`\[`int`]]]
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**Returns**
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The circuit $Q^k X |0\rangle$.
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</Function>
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### estimate
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<Function id="qiskit.algorithms.FasterAmplitudeEstimation.estimate" signature="FasterAmplitudeEstimation.estimate(estimation_problem)">
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Run the amplitude estimation algorithm.
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**Parameters**
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**estimation\_problem** (`EstimationProblem`) – An `EstimationProblem` containing all problem-relevant information such as the state preparation and the objective qubits.
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**Return type**
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`FasterAmplitudeEstimationResult`
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</Function>
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## Attributes
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### quantum\_instance
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<Attribute id="qiskit.algorithms.FasterAmplitudeEstimation.quantum_instance">
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Get the quantum instance.
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**Return type**
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`Optional`\[`QuantumInstance`]
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**Returns**
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The quantum instance used to run this algorithm.
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</Attribute>
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</Class>
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