def test_unitary_channel_errors():
"""Check errors raised by ``gates.UnitaryChannel``."""
a1 = np.array([[0, 1], [1, 0]])
a2 = np.array([[1, 0, 0, 0], [0, 1, 0, 0], [0, 0, 0, 1], [0, 0, 1, 0]])
probs = [0.4, 0.3]
matrices = [((0, ), a1), ((2, 3), a2)]
# Invalid probability length
with pytest.raises(ValueError):
gate = gates.UnitaryChannel([0.1, 0.3, 0.2], matrices)
# Probability > 1
with pytest.raises(ValueError):
gate = gates.UnitaryChannel([1.1, 0.2], matrices)
# Probability sum = 0
with pytest.raises(ValueError):
gate = gates.UnitaryChannel([0.0, 0.0], matrices)
def test_unitary_channel(backend):
a1 = np.array([[0, 1], [1, 0]])
a2 = np.array([[1, 0, 0, 0], [0, 1, 0, 0], [0, 0, 0, 1], [0, 0, 1, 0]])
probs = [0.4, 0.3]
matrices = [((0, ), a1), ((2, 3), a2)]
initial_state = random_density_matrix(4)
gate = gates.UnitaryChannel(probs, matrices)
gate.density_matrix = True
final_state = gate(K.cast(np.copy(initial_state)))
eye = np.eye(2)
ma1 = np.kron(np.kron(a1, eye), np.kron(eye, eye))
ma2 = np.kron(np.kron(eye, eye), a2)
target_state = (0.3 * initial_state +
0.4 * ma1.dot(initial_state.dot(ma1)) +
0.3 * ma2.dot(initial_state.dot(ma2)))
K.assert_allclose(final_state, target_state)
def test_unitary_channel_probability_tolerance(backend, precision):
"""Create ``UnitaryChannel`` with probability sum within tolerance (see #562)."""
import qibo
original_precision = qibo.get_precision()
qibo.set_precision(precision)
nqubits = 2
param = 0.006
num_terms = 2**(2 * nqubits)
max_param = num_terms / (num_terms - 1)
prob_identity = 1 - param / max_param
prob_pauli = param / num_terms
probs = [prob_identity] + [prob_pauli] * (num_terms - 1)
if precision == "double":
probs = np.array(probs, dtype="float64")
else:
probs = np.array(probs, dtype="float32")
matrices = len(probs) * [((0, 1), np.random.random((4, 4)))]
gate = gates.UnitaryChannel(probs, matrices)
qibo.set_precision(original_precision)
def test_unitary_channel(backend, density_matrix):
"""Test creating `gates.UnitaryChannel` from matrices and errors."""
original_backend = qibo.get_backend()
qibo.set_backend(backend)
a1 = np.array([[0, 1], [1, 0]])
a2 = np.array([[1, 0, 0, 0], [0, 1, 0, 0], [0, 0, 0, 1], [0, 0, 1, 0]])
probs = [0.4, 0.3]
matrices = [((0, ), a1), ((2, 3), a2)]
if density_matrix:
initial_state = utils.random_density_matrix(4)
else:
initial_state = utils.random_numpy_state(4)
c = models.Circuit(4, density_matrix=density_matrix)
c.add(gates.UnitaryChannel(probs, matrices, seed=123))
final_state = c(initial_state, nshots=20).numpy()
eye = np.eye(2, dtype=final_state.dtype)
ma1 = np.kron(np.kron(a1, eye), np.kron(eye, eye))
ma2 = np.kron(np.kron(eye, eye), a2)
if density_matrix:
# use density matrices
target_state = (0.3 * initial_state +
0.4 * ma1.dot(initial_state.dot(ma1)) +
0.3 * ma2.dot(initial_state.dot(ma2)))
else:
# sample unitary channel
target_state = []
np.random.seed(123)
for _ in range(20):
temp_state = np.copy(initial_state)
if np.random.random() < 0.4:
temp_state = ma1.dot(temp_state)
if np.random.random() < 0.3:
temp_state = ma2.dot(temp_state)
target_state.append(np.copy(temp_state))
np.testing.assert_allclose(final_state, target_state)
qibo.set_backend(original_backend)
