78 lines
3.7 KiB
Plaintext
78 lines
3.7 KiB
Plaintext
---
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title: SPSASamplerGradient
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description: API reference for qiskit.algorithms.gradients.SPSASamplerGradient
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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.SPSASamplerGradient
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---
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# SPSASamplerGradient
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<Class id="qiskit.algorithms.gradients.SPSASamplerGradient" isDedicatedPage={true} github="https://github.com/qiskit/qiskit/tree/stable/0.22/qiskit/algorithms/gradients/spsa_sampler_gradient.py" signature="SPSASamplerGradient(sampler, epsilon, batch_size=1, seed=None, **options)" modifiers="class">
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Bases: [`qiskit.algorithms.gradients.base_sampler_gradient.BaseSamplerGradient`](qiskit.algorithms.gradients.BaseSamplerGradient "qiskit.algorithms.gradients.base_sampler_gradient.BaseSamplerGradient")
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Compute the gradients of the sampling probability by the Simultaneous Perturbation Stochastic Approximation (SPSA).
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**Parameters**
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* **sampler** ([*BaseSampler*](qiskit.primitives.BaseSampler "qiskit.primitives.BaseSampler")) – The sampler used to compute the gradients.
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* **epsilon** (*float*) – The offset size for the SPSA gradients.
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* **batch\_size** (*int*) – number of gradients to average.
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* **seed** (*int | None*) – The seed for a random perturbation vector.
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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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**Raises**
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**ValueError** – If `epsilon` is not positive.
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## Methods
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### run
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<Function id="qiskit.algorithms.gradients.SPSASamplerGradient.run" signature="SPSASamplerGradient.run(circuits, parameter_values, parameters=None, **options)">
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Run the job of the sampler 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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* **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 sampling probability. The i-th result corresponds to `circuits[i]` evaluated with parameters bound as `parameter_values[i]`. The j-th quasi-probability distribution in the i-th result corresponds to the gradients of the sampling probability for the j-th parameter in `circuits[i]`.
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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.SPSASamplerGradient.update_default_options" signature="SPSASamplerGradient.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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### options
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<Attribute id="qiskit.algorithms.gradients.SPSASamplerGradient.options">
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Return the union of sampler 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 + sampler options.
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</Attribute>
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</Class>
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