def test_kraus_matrices_valid(self):
"""Tests that the given Kraus matrices are valid"""
# check all Kraus matrices are square matrices
K_list1 = [np.zeros((2, 2)), np.zeros((2, 3))]
with pytest.raises(
ValueError,
match=
"Only channels with the same input and output Hilbert space"):
channel.QubitChannel(K_list1, wires=0)
# check all Kraus matrices have the same shape
K_list2 = [np.eye(2), np.eye(4)]
with pytest.raises(
ValueError,
match="All Kraus matrices must have the same shape."):
channel.QubitChannel(K_list2, wires=0)
# check the dimension of all Kraus matrices are valid
K_list3 = [
np.array([np.eye(2), np.eye(2)]),
np.array([np.eye(2), np.eye(2)])
]
with pytest.raises(ValueError,
match="Dimension of all Kraus matrices must be "):
channel.QubitChannel(K_list3, wires=0)
def test_channel_trace_preserving(self):
"""Tests that the channel represents a trace-preserving map"""
# real Kraus matrices
K_list1 = [
np.array([[1.0, 0.0], [0.0, 0.9486833]]),
np.array([[0.0, 0.31622777], [0.0, 0.0]]),
]
with pytest.raises(ValueError, match="Only trace preserving channels can be applied."):
channel.QubitChannel(K_list1 * 2, wires=0)
# complex Kraus matrices
p = 0.1
K_list2 = [np.sqrt(p) * Y, np.sqrt(1 - p) * np.eye(2)]
with pytest.raises(ValueError, match="Only trace preserving channels can be applied."):
channel.QubitChannel(K_list2 * 2, wires=0)
def test_input_correctly_handled(self, tol):
"""Test that Kraus matrices are correctly processed"""
K_list1 = [
np.array([[1.0, 0.0], [0.0, 0.9486833]]),
np.array([[0.0, 0.31622777], [0.0, 0.0]]),
]
out = channel.QubitChannel(K_list1, wires=0).kraus_matrices
# verify equivalent to input matrices
assert np.allclose(out, K_list1, atol=tol, rtol=0)
