def build_measurement_error_mitigation_qobj(
qubit_list: List[int],
fitter_cls: Callable,
backend: Backend,
backend_config: Optional[Dict] = None,
compile_config: Optional[Dict] = None,
run_config: Optional[RunConfig] = None,
mit_pattern: Optional[List[List[int]]] = None,
) -> Tuple[QasmQobj, List[str], List[str]]:
"""
Args:
qubit_list: list of ordered qubits used in the algorithm
fitter_cls: CompleteMeasFitter or TensoredMeasFitter
backend: backend instance
backend_config: configuration for backend
compile_config: configuration for compilation
run_config: configuration for running a circuit
mit_pattern: Qubits on which to perform the
measurement correction, divided to groups according to tensors.
If `None` and `qr` is given then assumed to be performed over the entire
`qr` as one group (default `None`).
Returns:
the Qobj with calibration circuits at the beginning
the state labels for build MeasFitter
the labels of the calibration circuits
Raises:
QiskitError: when the fitter_cls is not recognizable.
MissingOptionalLibraryError: Qiskit-Ignis not installed
"""
circlabel = "mcal"
if not qubit_list:
raise QiskitError("The measured qubit list can not be [].")
if fitter_cls == CompleteMeasFitter:
meas_calibs_circuits, state_labels = complete_meas_cal(
qubit_list=range(len(qubit_list)), circlabel=circlabel
)
elif fitter_cls == TensoredMeasFitter:
meas_calibs_circuits, state_labels = tensored_meas_cal(
mit_pattern=mit_pattern, circlabel=circlabel
)
else:
raise QiskitError(f"Unknown fitter {fitter_cls}")
# the provided `qubit_list` would be used as the initial layout to
# assure the consistent qubit mapping used in the main circuits.
tmp_compile_config = copy.deepcopy(compile_config)
tmp_compile_config["initial_layout"] = qubit_list
t_meas_calibs_circuits = compiler.transpile(
meas_calibs_circuits, backend, **backend_config, **tmp_compile_config
)
cals_qobj = compiler.assemble(t_meas_calibs_circuits, backend, **run_config.to_dict())
if hasattr(cals_qobj.config, "parameterizations"):
del cals_qobj.config.parameterizations
return cals_qobj, state_labels, circlabel
def tensored_calib_circ_creation():
"""
create tensored measurement calibration circuits and a GHZ state circuit for the tests
Returns:
QuantumCircuit: the tensored measurement calibration circuit
list[list[int]]: the mitigation pattern
QuantumCircuit: ghz circuit with 5 qubits (3 are used)
"""
mit_pattern = [[2], [4, 1]]
meas_layout = [2, 4, 1]
qr = qiskit.QuantumRegister(5)
# Generate the calibration circuits
meas_calibs, mit_pattern = tensored_meas_cal(mit_pattern, qr=qr)
cr = qiskit.ClassicalRegister(3)
ghz_circ = qiskit.QuantumCircuit(qr, cr)
ghz_circ.h(mit_pattern[0][0])
ghz_circ.cx(mit_pattern[0][0], mit_pattern[1][0])
ghz_circ.cx(mit_pattern[0][0], mit_pattern[1][1])
ghz_circ.measure(mit_pattern[0][0], cr[0])
ghz_circ.measure(mit_pattern[1][0], cr[1])
ghz_circ.measure(mit_pattern[1][1], cr[2])
return meas_calibs, mit_pattern, ghz_circ, meas_layout
def test_ideal_tensored_meas_cal(self):
"""Test ideal execution, without noise."""
mit_pattern = [[1, 2], [3, 4, 5], [6]]
meas_layout = [1, 2, 3, 4, 5, 6]
# Generate the calibration circuits
meas_calibs, _ = tensored_meas_cal(mit_pattern=mit_pattern)
# Perform an ideal execution on the generated circuits
backend = Aer.get_backend("qasm_simulator")
cal_results = qiskit.execute(meas_calibs,
backend=backend,
shots=self.shots).result()
# Make calibration matrices
meas_cal = TensoredMeasFitter(cal_results, mit_pattern=mit_pattern)
# Assert that the calibration matrices are equal to identity
cal_matrices = meas_cal.cal_matrices
self.assertEqual(len(mit_pattern), len(cal_matrices),
"Wrong number of calibration matrices")
for qubit_list, cal_mat in zip(mit_pattern, cal_matrices):
IdentityMatrix = np.identity(2**len(qubit_list))
self.assertListEqual(
cal_mat.tolist(),
IdentityMatrix.tolist(),
"Error: the calibration matrix is not equal to identity",
)
# Assert that the readout fidelity is equal to 1
self.assertEqual(
meas_cal.readout_fidelity(),
1.0,
"Error: the average fidelity is not equal to 1",
)
# Generate ideal (equally distributed) results
results_dict, _ = self.generate_ideal_results(count_keys(6), 6)
# Output the filter
meas_filter = meas_cal.filter
# Apply the calibration matrix to results
# in list and dict forms using different methods
results_dict_1 = meas_filter.apply(results_dict,
method="least_squares",
meas_layout=meas_layout)
results_dict_0 = meas_filter.apply(results_dict,
method="pseudo_inverse",
meas_layout=meas_layout)
# Assert that the results are equally distributed
self.assertDictEqual(results_dict, results_dict_0)
round_results = {}
for key, val in results_dict_1.items():
round_results[key] = np.round(val)
self.assertDictEqual(results_dict, round_results)
def build_measurement_error_mitigation_circuits(
qubit_list: List[int],
fitter_cls: Callable,
backend: Backend,
backend_config: Optional[Dict] = None,
compile_config: Optional[Dict] = None,
mit_pattern: Optional[List[List[int]]] = None,
) -> Tuple[QuantumCircuit, List[str], List[str]]:
"""Build measurement error mitigation circuits
Args:
qubit_list: list of ordered qubits used in the algorithm
fitter_cls: CompleteMeasFitter or TensoredMeasFitter
backend: backend instance
backend_config: configuration for backend
compile_config: configuration for compilation
mit_pattern: Qubits on which to perform the
measurement correction, divided to groups according to tensors.
If `None` and `qr` is given then assumed to be performed over the entire
`qr` as one group (default `None`).
Returns:
the circuit
the state labels for build MeasFitter
the labels of the calibration circuits
Raises:
QiskitError: when the fitter_cls is not recognizable.
"""
circlabel = "mcal"
if not qubit_list:
raise QiskitError("The measured qubit list can not be [].")
run = False
if fitter_cls == CompleteMeasFitter:
meas_calibs_circuits, state_labels = complete_meas_cal(
qubit_list=range(len(qubit_list)), circlabel=circlabel
)
run = True
elif fitter_cls == TensoredMeasFitter:
meas_calibs_circuits, state_labels = tensored_meas_cal(
mit_pattern=mit_pattern, circlabel=circlabel
)
run = True
if not run:
try:
from qiskit.ignis.mitigation.measurement import (
CompleteMeasFitter as CompleteMeasFitter_IG,
TensoredMeasFitter as TensoredMeasFitter_IG,
)
except ImportError as ex:
# If ignis can't be imported we don't have a valid fitter
# class so just fail here with an appropriate error message
raise QiskitError(f"Unknown fitter {fitter_cls}") from ex
if fitter_cls == CompleteMeasFitter_IG:
meas_calibs_circuits, state_labels = complete_meas_cal(
qubit_list=range(len(qubit_list)), circlabel=circlabel
)
elif fitter_cls == TensoredMeasFitter_IG:
meas_calibs_circuits, state_labels = tensored_meas_cal(
mit_pattern=mit_pattern, circlabel=circlabel
)
else:
raise QiskitError(f"Unknown fitter {fitter_cls}")
# the provided `qubit_list` would be used as the initial layout to
# assure the consistent qubit mapping used in the main circuits.
tmp_compile_config = copy.deepcopy(compile_config)
tmp_compile_config["initial_layout"] = qubit_list
t_meas_calibs_circuits = compiler.transpile(
meas_calibs_circuits, backend, **backend_config, **tmp_compile_config
)
return t_meas_calibs_circuits, state_labels, circlabel