def test_outcome_probabilities_cntrl(self):
for _ in range(100):
qc = QC(4, 0, probabilistic=True)
qc.create_bell_pair(0, 1)
qc.CZ(0, 2)
outcome = qc.measure([1, 0])
self.assertEqual(outcome[0], outcome[1])
def test_outcome_probabilities_CZ(self):
for _ in range(100):
qc = QC(4, 0, probabilistic=True)
qc.create_bell_pair(0, 1)
qc.CZ(1, 0)
outcome = qc.measure([1, 0])
self.assertFalse(outcome[0] == outcome[1])
def test_outcome_probabilities_single_selection(self):
for _ in range(100):
qc = QC(4, 0, probabilistic=True)
qc.create_bell_pair(3, 1)
qc.create_bell_pair(2, 0)
qc.CZ(0, 1)
qc.CZ(2, 3)
outcome = qc.measure([0, 2])
self.assertEqual(outcome[0], outcome[1])
def test_outcome_probabilities_single_dot(self):
for _ in range(100):
qc = QC(6, 0, probabilistic=True)
qc.create_bell_pair(5, 2)
qc.create_bell_pair(4, 1)
qc.single_selection(CNOT_gate, 3, 0)
qc.single_selection(CZ_gate, 3, 0)
qc.CZ(4, 5)
qc.CZ(1, 2)
outcomes = qc.measure([1, 4])
self.assertEqual(outcomes[0], outcomes[1])
bell_matrix = 1 / 2 * np.array([[1, 0, 0, 1], [0, 0, 0, 0],
[0, 0, 0, 0], [1, 0, 0, 1]])
np.testing.assert_array_equal(
qc._qubit_density_matrix_lookup[5][0].toarray(), bell_matrix)