48 lines
2.0 KiB
Plaintext
48 lines
2.0 KiB
Plaintext
---
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title: CircuitQFI (v0.29)
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description: API reference for qiskit.aqua.operators.gradients.CircuitQFI in qiskit v0.29
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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.aqua.operators.gradients.CircuitQFI
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---
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# CircuitQFI
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<Class id="qiskit.aqua.operators.gradients.CircuitQFI" isDedicatedPage={true} github="https://github.com/qiskit-community/qiskit-aqua/tree/stable/0.9/qiskit/aqua/operators/gradients/circuit_qfis/circuit_qfi.py" signature="CircuitQFI" modifiers="class">
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Bases: `qiskit.aqua.operators.converters.converter_base.ConverterBase`
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Circuit to Quantum Fisher Information operator converter.
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Converter for changing parameterized circuits into operators whose evaluation yields Quantum Fisher Information metric tensor with respect to the given circuit parameters
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This is distinct from DerivativeBase converters which take gradients of composite operators and handle things like differentiating combo\_fn’s and enforcing product rules when operator coefficients are parameterized.
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CircuitQFI - uses quantum techniques to get the QFI of circuits DerivativeBase - uses classical techniques to differentiate opflow data structures
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## Methods
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<span id="qiskit-aqua-operators-gradients-circuitqfi-convert" />
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### convert
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<Function id="qiskit.aqua.operators.gradients.CircuitQFI.convert" signature="CircuitQFI.convert(operator, params=None)" modifiers="abstract">
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**Parameters**
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* **operator** (`OperatorBase`) – The operator corresponding to the quantum state $|\psi(\omega)\rangle$ for which we compute the QFI.
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* **params** (`Union`\[`ParameterVector`, `ParameterExpression`, `List`\[`ParameterExpression`], `None`]) – The parameters $\omega$ with respect to which we are computing the QFI.
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**Return type**
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`OperatorBase`
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**Returns**
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An operator whose evaluation yields the QFI metric tensor.
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**Raises**
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**ValueError** – If `params` contains a parameter not present in `operator`.
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</Function>
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</Class>
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