101 lines
4.6 KiB
Plaintext
101 lines
4.6 KiB
Plaintext
---
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title: ReverseEstimatorGradient
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description: API reference for qiskit.algorithms.gradients.ReverseEstimatorGradient
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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.gradients.ReverseEstimatorGradient
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---
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# ReverseEstimatorGradient
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<Class id="qiskit.algorithms.gradients.ReverseEstimatorGradient" isDedicatedPage={true} github="https://github.com/qiskit/qiskit/tree/stable/0.23/qiskit/algorithms/gradients/reverse_gradient/reverse_gradient.py" signature="ReverseEstimatorGradient(derivative_type=DerivativeType.REAL)" modifiers="class">
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Bases: [`qiskit.algorithms.gradients.base_estimator_gradient.BaseEstimatorGradient`](qiskit.algorithms.gradients.BaseEstimatorGradient "qiskit.algorithms.gradients.base_estimator_gradient.BaseEstimatorGradient")
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Estimator gradients with the classically efficient reverse mode.
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<Admonition title="Note" type="note">
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This gradient implementation is based on statevector manipulations and scales exponentially with the number of qubits. However, for small system sizes it can be very fast compared to circuit-based gradients.
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</Admonition>
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This class implements the calculation of the expectation gradient as described in \[1]. By keeping track of two statevectors and iteratively sweeping through each parameterized gate, this method scales only linearly with the number of parameters.
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**References:**
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> **\[1]: Jones, T. and Gacon, J. “Efficient calculation of gradients in classical simulations**
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>
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> of variational quantum algorithms” (2020). [arXiv:2009.02823](https://arxiv.org/abs/2009.02823).
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**Parameters**
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**derivative\_type** ([`DerivativeType`](qiskit.algorithms.gradients.DerivativeType "qiskit.algorithms.gradients.utils.DerivativeType")) – Defines whether the real, imaginary or real plus imaginary part of the gradient is returned.
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## Methods
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### run
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<Function id="qiskit.algorithms.gradients.ReverseEstimatorGradient.run" signature="ReverseEstimatorGradient.run(circuits, observables, parameter_values, parameters=None, **options)">
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Run the job of the estimator gradient on the given circuits.
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**Parameters**
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* **circuits** – The list of quantum circuits to compute the gradients.
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* **observables** – The list of observables.
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* **parameter\_values** – The list of parameter values to be bound to the circuit.
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* **parameters** – The sequence of parameters to calculate only the gradients of the specified parameters. Each sequence of parameters corresponds to a circuit in `circuits`. Defaults to None, which means that the gradients of all parameters in each circuit are calculated.
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* **options** – Primitive backend runtime options used for circuit execution. The order of priority is: options in `run` method > gradient’s default options > primitive’s default setting. Higher priority setting overrides lower priority setting
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**Returns**
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The job object of the gradients of the expectation values. The i-th result corresponds to `circuits[i]` evaluated with parameters bound as `parameter_values[i]`. The j-th element of the i-th result corresponds to the gradient of the i-th circuit with respect to the j-th parameter.
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**Raises**
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**ValueError** – Invalid arguments are given.
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</Function>
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### update\_default\_options
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<Function id="qiskit.algorithms.gradients.ReverseEstimatorGradient.update_default_options" signature="ReverseEstimatorGradient.update_default_options(**options)">
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Update the gradient’s default options setting.
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**Parameters**
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**\*\*options** – The fields to update the default options.
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</Function>
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## Attributes
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### SUPPORTED\_GATES
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<Attribute id="qiskit.algorithms.gradients.ReverseEstimatorGradient.SUPPORTED_GATES" attributeValue="['rx', 'ry', 'rz', 'cp', 'crx', 'cry', 'crz']" />
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### derivative\_type
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<Attribute id="qiskit.algorithms.gradients.ReverseEstimatorGradient.derivative_type">
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Return the derivative type (real, imaginary or complex).
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**Return type**
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[`DerivativeType`](qiskit.algorithms.gradients.DerivativeType "qiskit.algorithms.gradients.utils.DerivativeType")
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**Returns**
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The derivative type.
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</Attribute>
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### options
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<Attribute id="qiskit.algorithms.gradients.ReverseEstimatorGradient.options">
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Return the union of estimator options setting and gradient default options, where, if the same field is set in both, the gradient’s default options override the primitive’s default setting.
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**Return type**
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[`Options`](qiskit.providers.Options "qiskit.providers.options.Options")
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**Returns**
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The gradient default + estimator options.
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</Attribute>
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</Class>
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