249 lines
12 KiB
Plaintext
249 lines
12 KiB
Plaintext
---
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title: CompleteExpvalMeasMitigator
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description: API reference for qiskit.ignis.mitigation.CompleteExpvalMeasMitigator
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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.ignis.mitigation.CompleteExpvalMeasMitigator
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---
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# qiskit.ignis.mitigation.CompleteExpvalMeasMitigator
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<Class id="qiskit.ignis.mitigation.CompleteExpvalMeasMitigator" isDedicatedPage={true} github="https://github.com/qiskit-community/qiskit-ignis/tree/stable/0.6/qiskit/ignis/mitigation/expval/complete_mitigator.py" signature="CompleteExpvalMeasMitigator(amat)" modifiers="class">
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N-qubit measurement error mitigator.
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This class can be used with the [`qiskit.ignis.mitigation.expectation_value()`](qiskit.ignis.mitigation.expectation_value "qiskit.ignis.mitigation.expectation_value") function to apply measurement error mitigation of general N-qubit measurement errors when calculating expectation values from counts. Expectation values can also be computed directly using the [`expectation_value()`](qiskit.ignis.mitigation.expectation_value "qiskit.ignis.mitigation.expectation_value") method.
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For measurement mitigation to be applied the mitigator should be calibrated using the [`qiskit.ignis.mitigation.expval_meas_mitigator_circuits()`](qiskit.ignis.mitigation.expval_meas_mitigator_circuits "qiskit.ignis.mitigation.expval_meas_mitigator_circuits") function and [`qiskit.ignis.mitigation.ExpvalMeasMitigatorFitter`](qiskit.ignis.mitigation.ExpvalMeasMitigatorFitter "qiskit.ignis.mitigation.ExpvalMeasMitigatorFitter") class with the `'complete'` mitigation method.
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Initialize a TensorMeasurementMitigator
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**Parameters**
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**amat** (*np.array*) – readout error assignment matrix.
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### \_\_init\_\_
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<Function id="qiskit.ignis.mitigation.CompleteExpvalMeasMitigator.__init__" signature="__init__(amat)">
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Initialize a TensorMeasurementMitigator
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**Parameters**
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**amat** (*np.array*) – readout error assignment matrix.
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</Function>
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## Methods
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| --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------- |
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| [`__init__`](#qiskit.ignis.mitigation.CompleteExpvalMeasMitigator.__init__ "qiskit.ignis.mitigation.CompleteExpvalMeasMitigator.__init__")(amat) | Initialize a TensorMeasurementMitigator |
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| [`assignment_fidelity`](#qiskit.ignis.mitigation.CompleteExpvalMeasMitigator.assignment_fidelity "qiskit.ignis.mitigation.CompleteExpvalMeasMitigator.assignment_fidelity")(\[qubits]) | Return the measurement assignment fidelity on the specified qubits. |
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| [`assignment_matrix`](#qiskit.ignis.mitigation.CompleteExpvalMeasMitigator.assignment_matrix "qiskit.ignis.mitigation.CompleteExpvalMeasMitigator.assignment_matrix")(\[qubits]) | Return the measurement assignment matrix for specified qubits. |
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| [`expectation_value`](#qiskit.ignis.mitigation.CompleteExpvalMeasMitigator.expectation_value "qiskit.ignis.mitigation.CompleteExpvalMeasMitigator.expectation_value")(counts\[, diagonal, …]) | Compute the mitigated expectation value of a diagonal observable. |
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| [`mitigation_matrix`](#qiskit.ignis.mitigation.CompleteExpvalMeasMitigator.mitigation_matrix "qiskit.ignis.mitigation.CompleteExpvalMeasMitigator.mitigation_matrix")(\[qubits]) | Return the measurement mitigation matrix for the specified qubits. |
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| [`mitigation_overhead`](#qiskit.ignis.mitigation.CompleteExpvalMeasMitigator.mitigation_overhead "qiskit.ignis.mitigation.CompleteExpvalMeasMitigator.mitigation_overhead")(\[qubits]) | Return the mitigation overhead for expectation value estimation. |
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| [`plot_assignment_matrix`](#qiskit.ignis.mitigation.CompleteExpvalMeasMitigator.plot_assignment_matrix "qiskit.ignis.mitigation.CompleteExpvalMeasMitigator.plot_assignment_matrix")(\[qubits, ax]) | Matrix plot of the readout error assignment matrix. |
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| [`plot_mitigation_matrix`](#qiskit.ignis.mitigation.CompleteExpvalMeasMitigator.plot_mitigation_matrix "qiskit.ignis.mitigation.CompleteExpvalMeasMitigator.plot_mitigation_matrix")(\[qubits, ax]) | Matrix plot of the readout error mitigation matrix. |
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| [`required_shots`](#qiskit.ignis.mitigation.CompleteExpvalMeasMitigator.required_shots "qiskit.ignis.mitigation.CompleteExpvalMeasMitigator.required_shots")(delta\[, qubits]) | Return the number of shots required for expectation value estimation. |
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| [`stddev_upper_bound`](#qiskit.ignis.mitigation.CompleteExpvalMeasMitigator.stddev_upper_bound "qiskit.ignis.mitigation.CompleteExpvalMeasMitigator.stddev_upper_bound")(\[shots, qubits]) | Return an upper bound on standard deviation of expval estimator. |
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### assignment\_fidelity
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<Function id="qiskit.ignis.mitigation.CompleteExpvalMeasMitigator.assignment_fidelity" signature="assignment_fidelity(qubits=None)">
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Return the measurement assignment fidelity on the specified qubits.
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The assignment fidelity on N-qubits is defined as $\sum_{x\in\{0, 1\}^n} P(x|x) / 2^n$, where $P(x|x) = \rangle x|A|x\langle$, and $A$ is the [`assignment_matrix()`](#qiskit.ignis.mitigation.CompleteExpvalMeasMitigator.assignment_matrix "qiskit.ignis.mitigation.CompleteExpvalMeasMitigator.assignment_matrix").
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**Parameters**
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**qubits** (`Optional`\[`List`\[`int`]]) – Optional, qubits being measured for operator expval.
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**Returns**
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the assignment fidelity.
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**Return type**
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float
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</Function>
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### assignment\_matrix
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<Function id="qiskit.ignis.mitigation.CompleteExpvalMeasMitigator.assignment_matrix" signature="assignment_matrix(qubits=None)">
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Return the measurement assignment matrix for specified qubits.
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The assignment matrix is the stochastic matrix $A$ which assigns a noisy measurement probability distribution to an ideal input measurement distribution: $P(i|j) = \langle i | A | j \rangle$.
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**Parameters**
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**qubits** (`Optional`\[`List`\[`int`]]) – Optional, qubits being measured for operator expval.
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**Returns**
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the assignment matrix A.
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**Return type**
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np.ndarray
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</Function>
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### expectation\_value
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<Function id="qiskit.ignis.mitigation.CompleteExpvalMeasMitigator.expectation_value" signature="expectation_value(counts, diagonal=None, qubits=None, clbits=None)">
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Compute the mitigated expectation value of a diagonal observable.
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This computes the mitigated estimator of $\langle O \rangle = \mbox{Tr}[\rho. O]$ of a diagonal observable $O = \sum_{x\in\{0, 1\}^n} O(x)|x\rangle\!\langle x|$.
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**Parameters**
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* **counts** (`Dict`) – counts object
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* **diagonal** (`Optional`\[`ndarray`]) – Optional, the vector of diagonal values for summing the expectation value. If `None` the the default value is $[1, -1]^\otimes n$.
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* **qubits** (`Optional`\[`List`\[`int`]]) – Optional, the measured physical qubits the count bitstrings correspond to. If None qubits are assumed to be $[0, ..., n-1]$.
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* **clbits** (`Optional`\[`List`\[`int`]]) – Optional, if not None marginalize counts to the specified bits.
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**Returns**
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the expectation value and standard deviation.
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**Return type**
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(float, float)
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**Raises**
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**QiskitError** – if input arguments are invalid.
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**Additional Information:**
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The diagonal observable $O$ is input using the `diagonal` kwarg as a list or Numpy array $[O(0), ..., O(2^n -1)]$. If no diagonal is specified the diagonal of the Pauli operator :math\`O = mbox\{diag}(Z^\{otimes n}) = \[1, -1]^\{otimes n}\` is used.
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The `clbits` kwarg is used to marginalize the input counts dictionary over the specified bit-values, and the `qubits` kwarg is used to specify which physical qubits these bit-values correspond to as `circuit.measure(qubits, clbits)`.
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</Function>
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### mitigation\_matrix
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<Function id="qiskit.ignis.mitigation.CompleteExpvalMeasMitigator.mitigation_matrix" signature="mitigation_matrix(qubits=None)">
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Return the measurement mitigation matrix for the specified qubits.
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The mitigation matrix $A^{-1}$ is defined as the inverse of the [`assignment_matrix()`](#qiskit.ignis.mitigation.CompleteExpvalMeasMitigator.assignment_matrix "qiskit.ignis.mitigation.CompleteExpvalMeasMitigator.assignment_matrix") $A$.
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**Parameters**
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**qubits** (`Optional`\[`List`\[`int`]]) – Optional, qubits being measured for operator expval.
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**Returns**
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the measurement error mitigation matrix $A^{-1}$.
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**Return type**
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np.ndarray
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</Function>
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### mitigation\_overhead
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<Function id="qiskit.ignis.mitigation.CompleteExpvalMeasMitigator.mitigation_overhead" signature="mitigation_overhead(qubits=None)">
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Return the mitigation overhead for expectation value estimation.
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This is the multiplicative factor of extra shots required for estimating a mitigated expectation value with the same accuracy as an unmitigated expectation value.
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**Parameters**
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**qubits** (`Optional`\[`List`\[`int`]]) – Optional, qubits being measured for operator expval.
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**Returns**
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the mitigation overhead factor.
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**Return type**
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int
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</Function>
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### plot\_assignment\_matrix
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<Function id="qiskit.ignis.mitigation.CompleteExpvalMeasMitigator.plot_assignment_matrix" signature="plot_assignment_matrix(qubits=None, ax=None)">
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Matrix plot of the readout error assignment matrix.
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**Parameters**
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* **qubits** (*list(int)*) – Optional, qubits being measured for operator expval.
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* **ax** (*axes*) – Optional. Axes object to add plot to.
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**Returns**
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the figure axes object.
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**Return type**
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plt.axes
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**Raises**
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**ImportError** – if matplotlib is not installed.
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</Function>
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### plot\_mitigation\_matrix
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<Function id="qiskit.ignis.mitigation.CompleteExpvalMeasMitigator.plot_mitigation_matrix" signature="plot_mitigation_matrix(qubits=None, ax=None)">
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Matrix plot of the readout error mitigation matrix.
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**Parameters**
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* **qubits** (*list(int)*) – Optional, qubits being measured for operator expval.
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* **ax** (*plt.axes*) – Optional. Axes object to add plot to.
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**Returns**
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the figure axes object.
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**Return type**
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plt.axes
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**Raises**
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**ImportError** – if matplotlib is not installed.
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</Function>
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### required\_shots
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<Function id="qiskit.ignis.mitigation.CompleteExpvalMeasMitigator.required_shots" signature="required_shots(delta, qubits=None)">
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Return the number of shots required for expectation value estimation.
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This is the number of shots required so that $|\langle O \rangle_{est} - \langle O \rangle_{true}| < \delta$ with high probability (at least 2/3) and is given by $4\delta^2 \Gamma^2$ where $\Gamma^2$ is the [`mitigation_overhead()`](#qiskit.ignis.mitigation.CompleteExpvalMeasMitigator.mitigation_overhead "qiskit.ignis.mitigation.CompleteExpvalMeasMitigator.mitigation_overhead").
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**Parameters**
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* **delta** (`float`) – Error tolerance for expectation value estimator.
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* **qubits** (`Optional`\[`List`\[`int`]]) – Optional, qubits being measured for operator expval.
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**Returns**
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the required shots.
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**Return type**
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int
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</Function>
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### stddev\_upper\_bound
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<Function id="qiskit.ignis.mitigation.CompleteExpvalMeasMitigator.stddev_upper_bound" signature="stddev_upper_bound(shots=1, qubits=None)">
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Return an upper bound on standard deviation of expval estimator.
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**Parameters**
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* **shots** (`int`) – Number of shots used for expectation value measurement.
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* **qubits** (`Optional`\[`List`\[`int`]]) – qubits being measured for operator expval.
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**Returns**
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the standard deviation upper bound.
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**Return type**
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float
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</Function>
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</Class>
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