def test_noise_model(kraus_model_I_dict, kraus_model_RX90_dict):
noise_model_dict = {
"gates": [kraus_model_I_dict, kraus_model_RX90_dict],
"assignment_probs": {"1": [[1.0, 0.0], [0.0, 1.0]], "0": [[1.0, 0.0], [0.0, 1.0]]},
}
nm = NoiseModel.from_dict(noise_model_dict)
km1 = KrausModel.from_dict(kraus_model_I_dict)
km2 = KrausModel.from_dict(kraus_model_RX90_dict)
assert nm == NoiseModel(gates=[km1, km2], assignment_probs={0: np.eye(2), 1: np.eye(2)})
assert nm.gates_by_name("I") == [km1]
assert nm.gates_by_name("RX") == [km2]
assert nm.to_dict() == noise_model_dict
def test_noise_model(kraus_model_I_dict, kraus_model_RX90_dict):
noise_model_dict = {'gates': [kraus_model_I_dict,
kraus_model_RX90_dict],
'assignment_probs': {'1': [[1.0, 0.0], [0.0, 1.0]],
'0': [[1.0, 0.0], [0.0, 1.0]]},
}
nm = NoiseModel.from_dict(noise_model_dict)
km1 = KrausModel.from_dict(kraus_model_I_dict)
km2 = KrausModel.from_dict(kraus_model_RX90_dict)
assert nm == NoiseModel(gates=[km1, km2],
assignment_probs={0: np.eye(2), 1: np.eye(2)})
assert nm.gates_by_name('I') == [km1]
assert nm.gates_by_name('RX') == [km2]
assert nm.to_dict() == noise_model_dict
def test_kraus_model():
km = KrausModel('I', (5., ), (0, 1), [np.array([[1 + 1j]])], 1.0)
d = km.to_dict()
assert d == OrderedDict([('gate', km.gate), ('params', km.params),
('targets', (0, 1)),
('kraus_ops', [[[[1.]], [[1.0]]]]),
('fidelity', 1.0)])
assert KrausModel.from_dict(d) == km
def test_kraus_model():
km = KrausModel("I", (5.0, ), (0, 1), [np.array([[1 + 1j]])], 1.0)
d = km.to_dict()
assert d == OrderedDict([
("gate", km.gate),
("params", km.params),
("targets", (0, 1)),
("kraus_ops", [[[[1.0]], [[1.0]]]]),
("fidelity", 1.0),
])
assert KrausModel.from_dict(d) == km
def test_kraus_model(kraus_model_I_dict):
km = KrausModel.from_dict(kraus_model_I_dict)
assert km == KrausModel(gate=kraus_model_I_dict['gate'],
params=kraus_model_I_dict['params'],
targets=kraus_model_I_dict['targets'],
kraus_ops=[
KrausModel.unpack_kraus_matrix(kraus_op)
for kraus_op in kraus_model_I_dict['kraus_ops']
],
fidelity=kraus_model_I_dict['fidelity'])
d = km.to_dict()
assert d == OrderedDict([('gate', km.gate), ('params', km.params),
('targets', (0, 1)),
('kraus_ops', [[[[1.]], [[1.0]]]]),
('fidelity', 1.0)])
def test_kraus_model_2(kraus_model_I_dict):
km = KrausModel.from_dict(kraus_model_I_dict)
assert km == KrausModel(
gate=kraus_model_I_dict["gate"],
params=kraus_model_I_dict["params"],
targets=kraus_model_I_dict["targets"],
kraus_ops=[
KrausModel.unpack_kraus_matrix(kraus_op)
for kraus_op in kraus_model_I_dict["kraus_ops"]
],
fidelity=kraus_model_I_dict["fidelity"],
)
d = km.to_dict()
assert d == OrderedDict([
("gate", km.gate),
("params", km.params),
("targets", (0, 1)),
("kraus_ops", [[[[1.0]], [[1.0]]]]),
("fidelity", 1.0),
])