def test_NoiseModelEqualityBitFlip(self):
'''
Checks that ``NoiseModel`` equality works for equivalent bit flip maps.
'''
prob = 0.5
fair_bit_flip = [
np.sqrt(prob) * np.array([[1, 0], [0, 1]]),
np.sqrt(1 - prob) * np.array([[0, 1], [1, 0]])
]
self.assertEqual(NoiseModel(fair_bit_flip), b_flip_map(prob))
def test_NoiseModelArgElementsShapeMismatch(self):
'''
``NoiseModel`` throws a ``WrongShapeError`` if
the shape of any of the matricies in the list of Kraus operators don't
match all the rest.
'''
kraus_ops_mismatch = [np.zeros((5, 2)), np.zeros((3, 17))]
someNoiseModel = NoiseModel()
self.assertRaises(WrongShapeError, NoiseModel, kraus_ops_mismatch)
self.assertRaises(WrongShapeError, someNoiseModel.setKrausOperators,
kraus_ops_mismatch)
def test_NoiseModelInequalityBitFlip(self):
'''
Checks that ``NoiseModel`` equality works for inequivalent bit flip
maps.
'''
prob_1 = 0.9
prob_2 = 0.4
unfair_bit_flip = [
np.sqrt(prob_1) * np.array([[1, 0], [0, 1]]),
np.sqrt(1 - prob_1) * np.array([[0, 1], [1, 0]])
]
self.assertNotEqual(NoiseModel(unfair_bit_flip), b_flip_map(prob_2))
def b_flip_map(prob=0.1):
'''
Bit flip.
Parameters
----------
prob : numeric, between 0 and 1
Probability characterizing the likelihood of the outcomes represented
by the various Kraus operators.
Returns
-------
NoiseModel
Container of ndarray matrix representations of the Kraus operators in
the corresponding quantum operation.
'''
static = np.sqrt(1 - prob) * np.array([[1, 0], [0, 1]])
flip = np.sqrt(prob) * np.array([[0, 1], [1, 0]])
return NoiseModel([static, flip])
def phase_map(prob=0.1):
'''
Phase damping.
Parameters
----------
prob : numeric, between 0 and 1
Probability characterizing the likelihood of the outcomes represented
by the various Kraus operators.
Returns
-------
NoiseModel
Container of ndarray matrix representations of the Kraus operators in
the corresponding quantum operation.
'''
phase_1 = np.array([[1, 0], [0, np.sqrt(1 - prob)]])
phase_2 = np.array([[0, 0], [0, np.sqrt(prob)]])
return NoiseModel([phase_1, phase_2])
def depolarization_map(prob=0.1):
'''
Depolarizing channel.
Parameters
----------
prob : numeric, between 0 and 1
Probability characterizing the likelihood of the outcomes represented
by the various Kraus operators.
Returns
-------
NoiseModel
Container of ndarray matrix representations of the Kraus operators in
the corresponding quantum operation.
'''
dep_i = np.sqrt(1 - 3.0 * prob / 4) * np.array([[1, 0], [0, 1]])
dep_x = np.sqrt(1.0 * prob / 4) * np.array([[0, 1], [1, 0]])
dep_y = np.sqrt(1.0 * prob / 4) * np.array([[0, -1j], [1j, 0]])
dep_z = np.sqrt(1.0 * prob / 4) * np.array([[1, 0], [0, -1]])
return NoiseModel([dep_i, dep_x, dep_y, dep_z])
def setUp(self):
self.test_noise_model = NoiseModel()