132 lines
4.4 KiB
Plaintext
132 lines
4.4 KiB
Plaintext
---
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title: AbsoluteAverage
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description: API reference for qiskit.algorithms.linear_solvers.AbsoluteAverage
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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.linear_solvers.AbsoluteAverage
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---
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# AbsoluteAverage
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<Class id="qiskit.algorithms.linear_solvers.AbsoluteAverage" isDedicatedPage={true} github="https://github.com/qiskit/qiskit/tree/stable/0.23/qiskit/algorithms/linear_solvers/observables/absolute_average.py" signature="AbsoluteAverage" modifiers="class">
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Bases: [`qiskit.algorithms.linear_solvers.observables.linear_system_observable.LinearSystemObservable`](qiskit.algorithms.linear_solvers.LinearSystemObservable "qiskit.algorithms.linear_solvers.observables.linear_system_observable.LinearSystemObservable")
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The deprecated observable for the absolute average of a linear system of equations solution.
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For a vector $x=(x_1,...,x_N)$, the absolute average is defined as $\left|\frac{1}{N}\sum_{i=1}^{N}x_i\right|$.
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Examples:
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```python
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import warnings
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import numpy as np
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from qiskit import QuantumCircuit
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from qiskit.algorithms.linear_solvers.observables.absolute_average import \
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AbsoluteAverage
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from qiskit.opflow import StateFn
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with warnings.catch_warnings():
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warnings.simplefilter('ignore')
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observable = AbsoluteAverage()
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vector = [1.0, -2.1, 3.2, -4.3]
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init_state = vector / np.linalg.norm(vector)
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num_qubits = int(np.log2(len(vector)))
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qc = QuantumCircuit(num_qubits)
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qc.isometry(init_state, list(range(num_qubits)), None)
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qc.append(observable.observable_circuit(num_qubits), list(range(num_qubits)))
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# Observable operator
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observable_op = observable.observable(num_qubits)
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state_vec = (~StateFn(observable_op) @ StateFn(qc)).eval()
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# Obtain result
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result = observable.post_processing(state_vec, num_qubits)
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# Obtain analytical evaluation
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exact = observable.evaluate_classically(init_state)
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```
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## Methods
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### evaluate\_classically
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<Function id="qiskit.algorithms.linear_solvers.AbsoluteAverage.evaluate_classically" signature="AbsoluteAverage.evaluate_classically(solution)">
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Evaluates the given observable on the solution to the linear system.
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**Parameters**
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**solution** (`Union`\[`array`, [`QuantumCircuit`](qiskit.circuit.QuantumCircuit "qiskit.circuit.quantumcircuit.QuantumCircuit")]) – The solution to the system as a numpy array or the circuit that prepares it.
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**Return type**
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`float`
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**Returns**
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The value of the observable.
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</Function>
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### observable
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<Function id="qiskit.algorithms.linear_solvers.AbsoluteAverage.observable" signature="AbsoluteAverage.observable(num_qubits)">
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The observable operator.
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**Parameters**
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**num\_qubits** (`int`) – The number of qubits on which the observable will be applied.
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**Return type**
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`Union`\[[`TensoredOp`](qiskit.opflow.list_ops.TensoredOp "qiskit.opflow.list_ops.tensored_op.TensoredOp"), `List`\[[`TensoredOp`](qiskit.opflow.list_ops.TensoredOp "qiskit.opflow.list_ops.tensored_op.TensoredOp")]]
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**Returns**
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The observable as a sum of Pauli strings.
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</Function>
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### observable\_circuit
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<Function id="qiskit.algorithms.linear_solvers.AbsoluteAverage.observable_circuit" signature="AbsoluteAverage.observable_circuit(num_qubits)">
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The circuit implementing the absolute average observable.
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**Parameters**
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**num\_qubits** (`int`) – The number of qubits on which the observable will be applied.
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**Return type**
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`Union`\[[`QuantumCircuit`](qiskit.circuit.QuantumCircuit "qiskit.circuit.quantumcircuit.QuantumCircuit"), `List`\[[`QuantumCircuit`](qiskit.circuit.QuantumCircuit "qiskit.circuit.quantumcircuit.QuantumCircuit")]]
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**Returns**
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The observable as a QuantumCircuit.
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</Function>
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### post\_processing
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<Function id="qiskit.algorithms.linear_solvers.AbsoluteAverage.post_processing" signature="AbsoluteAverage.post_processing(solution, num_qubits, scaling=1)">
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Evaluates the absolute average on the solution to the linear system.
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**Parameters**
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* **solution** (`Union`\[`float`, `List`\[`float`]]) – The probability calculated from the circuit and the observable.
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* **num\_qubits** (`int`) – The number of qubits where the observable was applied.
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* **scaling** (`float`) – Scaling of the solution.
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**Return type**
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`float`
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**Returns**
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The value of the absolute average.
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**Raises**
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**ValueError** – If the input is not in the correct format.
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</Function>
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</Class>
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