312 lines
11 KiB
Plaintext
312 lines
11 KiB
Plaintext
---
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title: LinearAmplitudeFunction
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description: API reference for qiskit.circuit.library.LinearAmplitudeFunction
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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.circuit.library.LinearAmplitudeFunction
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---
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# LinearAmplitudeFunction
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<Class id="qiskit.circuit.library.LinearAmplitudeFunction" isDedicatedPage={true} github="https://github.com/qiskit/qiskit/tree/stable/0.21/qiskit/circuit/library/arithmetic/linear_amplitude_function.py" signature="LinearAmplitudeFunction(num_state_qubits, slope, offset, domain, image, rescaling_factor=1, breakpoints=None, name='F')" modifiers="class">
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Bases: [`qiskit.circuit.quantumcircuit.QuantumCircuit`](qiskit.circuit.QuantumCircuit "qiskit.circuit.quantumcircuit.QuantumCircuit")
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A circuit implementing a (piecewise) linear function on qubit amplitudes.
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An amplitude function $F$ of a function $f$ is a mapping
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$$
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F|x\rangle|0\rangle = \sqrt{1 - \hat{f}(x)} |x\rangle|0\rangle + \sqrt{\hat{f}(x)}
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|x\rangle|1\rangle.
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$$
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for a function $\hat{f}: \{ 0, ..., 2^n - 1 \} \rightarrow [0, 1]$, where $|x\rangle$ is a $n$ qubit state.
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This circuit implements $F$ for piecewise linear functions $\hat{f}$. In this case, the mapping $F$ can be approximately implemented using a Taylor expansion and linearly controlled Pauli-Y rotations, see \[1, 2] for more detail. This approximation uses a `rescaling_factor` to determine the accuracy of the Taylor expansion.
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In general, the function of interest $f$ is defined from some interval $[a,b]$, the `domain` to $[c,d]$, the `image`, instead of $\{ 1, ..., N \}$ to $[0, 1]$. Using an affine transformation we can rescale $f$ to $\hat{f}$:
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$$
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\hat{f}(x) = \frac{f(\phi(x)) - c}{d - c}
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$$
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with
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$$
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\phi(x) = a + \frac{b - a}{2^n - 1} x.
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$$
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If $f$ is a piecewise linear function on $m$ intervals $[p_{i-1}, p_i], i \in \{1, ..., m\}$ with slopes $\alpha_i$ and offsets $\beta_i$ it can be written as
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$$
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f(x) = \sum_{i=1}^m 1_{[p_{i-1}, p_i]}(x) (\alpha_i x + \beta_i)
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$$
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where $1_{[a, b]}$ is an indication function that is 1 if the argument is in the interval $[a, b]$ and otherwise 0. The breakpoints $p_i$ can be specified by the `breakpoints` argument.
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**References**
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**\[1]: Woerner, S., & Egger, D. J. (2018).**
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Quantum Risk Analysis. [arXiv:1806.06893](http://arxiv.org/abs/1806.06893)
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**\[2]: Gacon, J., Zoufal, C., & Woerner, S. (2020).**
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Quantum-Enhanced Simulation-Based Optimization. [arXiv:2005.10780](http://arxiv.org/abs/2005.10780)
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**Parameters**
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* **num\_state\_qubits** (`int`) – The number of qubits used to encode the variable $x$.
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* **slope** (`Union`\[`float`, `List`\[`float`]]) – The slope of the linear function. Can be a list of slopes if it is a piecewise linear function.
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* **offset** (`Union`\[`float`, `List`\[`float`]]) – The offset of the linear function. Can be a list of offsets if it is a piecewise linear function.
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* **domain** (`Tuple`\[`float`, `float`]) – The domain of the function as tuple $(x_\min{}, x_\max{})$.
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* **image** (`Tuple`\[`float`, `float`]) – The image of the function as tuple $(f_\min{}, f_\max{})$.
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* **rescaling\_factor** (`float`) – The rescaling factor to adjust the accuracy in the Taylor approximation.
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* **breakpoints** (`Optional`\[`List`\[`float`]]) – The breakpoints if the function is piecewise linear. If None, the function is not piecewise.
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* **name** (`str`) – Name of the circuit.
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## Methods Defined Here
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### post\_processing
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<Function id="qiskit.circuit.library.LinearAmplitudeFunction.post_processing" signature="LinearAmplitudeFunction.post_processing(scaled_value)">
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Map the function value of the approximated $\hat{f}$ to $f$.
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**Parameters**
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**scaled\_value** (`float`) – A function value from the Taylor expansion of $\hat{f}(x)$.
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**Return type**
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`float`
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**Returns**
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The `scaled_value` mapped back to the domain of $f$, by first inverting the transformation used for the Taylor approximation and then mapping back from $[0, 1]$ to the original domain.
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</Function>
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## Attributes
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### ancillas
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<Attribute id="qiskit.circuit.library.LinearAmplitudeFunction.ancillas">
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Returns a list of ancilla bits in the order that the registers were added.
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**Return type**
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`List`\[[`AncillaQubit`](qiskit.circuit.AncillaQubit "qiskit.circuit.quantumregister.AncillaQubit")]
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</Attribute>
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### calibrations
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<Attribute id="qiskit.circuit.library.LinearAmplitudeFunction.calibrations">
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Return calibration dictionary.
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**The custom pulse definition of a given gate is of the form**
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\{‘gate\_name’: \{(qubits, params): schedule}}
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**Return type**
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`dict`
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</Attribute>
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### clbits
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<Attribute id="qiskit.circuit.library.LinearAmplitudeFunction.clbits">
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Returns a list of classical bits in the order that the registers were added.
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**Return type**
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`List`\[[`Clbit`](qiskit.circuit.Clbit "qiskit.circuit.classicalregister.Clbit")]
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</Attribute>
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### data
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<Attribute id="qiskit.circuit.library.LinearAmplitudeFunction.data">
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Return the circuit data (instructions and context).
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**Returns**
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a list-like object containing the [`CircuitInstruction`](qiskit.circuit.CircuitInstruction "qiskit.circuit.CircuitInstruction")s for each instruction.
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**Return type**
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QuantumCircuitData
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</Attribute>
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### extension\_lib
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<Attribute id="qiskit.circuit.library.LinearAmplitudeFunction.extension_lib" attributeValue="'include "qelib1.inc";'" />
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### global\_phase
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<Attribute id="qiskit.circuit.library.LinearAmplitudeFunction.global_phase">
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Return the global phase of the circuit in radians.
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**Return type**
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`Union`\[[`ParameterExpression`](qiskit.circuit.ParameterExpression "qiskit.circuit.parameterexpression.ParameterExpression"), `float`]
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</Attribute>
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### header
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<Attribute id="qiskit.circuit.library.LinearAmplitudeFunction.header" attributeValue="'OPENQASM 2.0;'" />
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### instances
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<Attribute id="qiskit.circuit.library.LinearAmplitudeFunction.instances" attributeValue="87" />
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### metadata
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<Attribute id="qiskit.circuit.library.LinearAmplitudeFunction.metadata">
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The user provided metadata associated with the circuit
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The metadata for the circuit is a user provided `dict` of metadata for the circuit. It will not be used to influence the execution or operation of the circuit, but it is expected to be passed between all transforms of the circuit (ie transpilation) and that providers will associate any circuit metadata with the results it returns from execution of that circuit.
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**Return type**
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`dict`
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</Attribute>
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### num\_ancillas
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<Attribute id="qiskit.circuit.library.LinearAmplitudeFunction.num_ancillas">
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Return the number of ancilla qubits.
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**Return type**
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`int`
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</Attribute>
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### num\_clbits
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<Attribute id="qiskit.circuit.library.LinearAmplitudeFunction.num_clbits">
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Return number of classical bits.
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**Return type**
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`int`
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</Attribute>
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### num\_parameters
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<Attribute id="qiskit.circuit.library.LinearAmplitudeFunction.num_parameters">
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The number of parameter objects in the circuit.
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**Return type**
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`int`
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</Attribute>
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### num\_qubits
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<Attribute id="qiskit.circuit.library.LinearAmplitudeFunction.num_qubits">
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Return number of qubits.
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**Return type**
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`int`
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</Attribute>
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### op\_start\_times
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<Attribute id="qiskit.circuit.library.LinearAmplitudeFunction.op_start_times">
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Return a list of operation start times.
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This attribute is enabled once one of scheduling analysis passes runs on the quantum circuit.
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**Return type**
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`List`\[`int`]
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**Returns**
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List of integers representing instruction start times. The index corresponds to the index of instruction in `QuantumCircuit.data`.
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**Raises**
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**AttributeError** – When circuit is not scheduled.
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</Attribute>
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### parameters
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<Attribute id="qiskit.circuit.library.LinearAmplitudeFunction.parameters">
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The parameters defined in the circuit.
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This attribute returns the [`Parameter`](qiskit.circuit.Parameter "qiskit.circuit.Parameter") objects in the circuit sorted alphabetically. Note that parameters instantiated with a [`ParameterVector`](qiskit.circuit.ParameterVector "qiskit.circuit.ParameterVector") are still sorted numerically.
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**Examples**
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The snippet below shows that insertion order of parameters does not matter.
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```python
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>>> from qiskit.circuit import QuantumCircuit, Parameter
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>>> a, b, elephant = Parameter("a"), Parameter("b"), Parameter("elephant")
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>>> circuit = QuantumCircuit(1)
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>>> circuit.rx(b, 0)
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>>> circuit.rz(elephant, 0)
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>>> circuit.ry(a, 0)
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>>> circuit.parameters # sorted alphabetically!
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ParameterView([Parameter(a), Parameter(b), Parameter(elephant)])
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```
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Bear in mind that alphabetical sorting might be unituitive when it comes to numbers. The literal “10” comes before “2” in strict alphabetical sorting.
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```python
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>>> from qiskit.circuit import QuantumCircuit, Parameter
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>>> angles = [Parameter("angle_1"), Parameter("angle_2"), Parameter("angle_10")]
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>>> circuit = QuantumCircuit(1)
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>>> circuit.u(*angles, 0)
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>>> circuit.draw()
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┌─────────────────────────────┐
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q: ┤ U(angle_1,angle_2,angle_10) ├
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└─────────────────────────────┘
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>>> circuit.parameters
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ParameterView([Parameter(angle_1), Parameter(angle_10), Parameter(angle_2)])
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```
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To respect numerical sorting, a [`ParameterVector`](qiskit.circuit.ParameterVector "qiskit.circuit.ParameterVector") can be used.
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```python
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```
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```python
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>>> from qiskit.circuit import QuantumCircuit, Parameter, ParameterVector
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>>> x = ParameterVector("x", 12)
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>>> circuit = QuantumCircuit(1)
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>>> for x_i in x:
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... circuit.rx(x_i, 0)
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>>> circuit.parameters
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ParameterView([
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ParameterVectorElement(x[0]), ParameterVectorElement(x[1]),
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ParameterVectorElement(x[2]), ParameterVectorElement(x[3]),
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..., ParameterVectorElement(x[11])
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])
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```
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**Return type**
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`ParameterView`
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**Returns**
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The sorted [`Parameter`](qiskit.circuit.Parameter "qiskit.circuit.Parameter") objects in the circuit.
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</Attribute>
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### prefix
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<Attribute id="qiskit.circuit.library.LinearAmplitudeFunction.prefix" attributeValue="'circuit'" />
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### qubits
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<Attribute id="qiskit.circuit.library.LinearAmplitudeFunction.qubits">
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Returns a list of quantum bits in the order that the registers were added.
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**Return type**
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`List`\[[`Qubit`](qiskit.circuit.Qubit "qiskit.circuit.quantumregister.Qubit")]
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</Attribute>
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</Class>
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