def test_thermal_error(backend, density_matrix):
thermal = ThermalRelaxationError(2, 1, 0.3)
noise = NoiseModel()
noise.add(thermal, gates.X, 1)
noise.add(thermal, gates.CNOT)
noise.add(thermal, gates.Z, (0,1))
circuit = Circuit(3, density_matrix=density_matrix)
circuit.add(gates.CNOT(0,1))
circuit.add(gates.Z(1))
circuit.add(gates.X(1))
circuit.add(gates.X(2))
circuit.add(gates.Z(2))
target_circuit = Circuit(3, density_matrix=density_matrix)
target_circuit.add(gates.CNOT(0,1))
target_circuit.add(gates.ThermalRelaxationChannel(0, 2, 1, 0.3))
target_circuit.add(gates.ThermalRelaxationChannel(1, 2, 1, 0.3))
target_circuit.add(gates.Z(1))
target_circuit.add(gates.ThermalRelaxationChannel(1, 2, 1, 0.3))
target_circuit.add(gates.X(1))
target_circuit.add(gates.ThermalRelaxationChannel(1, 2, 1, 0.3))
target_circuit.add(gates.X(2))
target_circuit.add(gates.Z(2))
initial_psi = random_density_matrix(3) if density_matrix else random_state(3)
np.random.seed(123)
K.set_seed(123)
final_state = noise.apply(circuit)(initial_state=np.copy(initial_psi))
np.random.seed(123)
K.set_seed(123)
target_final_state = target_circuit(initial_state=np.copy(initial_psi))
K.assert_allclose(final_state, target_final_state)
def test_thermal_relaxation_channel_repeated(backend):
original_backend = qibo.get_backend()
qibo.set_backend(backend)
initial_state = random_state(5)
c = Circuit(5)
c.add(gates.ThermalRelaxationChannel(4, t1=1.0, t2=0.6, time=0.8,
excited_population=0.8, seed=123))
final_state = c(np.copy(initial_state), nshots=30)
pz, p0, p1 = c.queue[0].calculate_probabilities(1.0, 0.6, 0.8, 0.8)
np.random.seed(123)
target_state = []
for _ in range(30):
noiseless_c = Circuit(5)
if np.random.random() < pz:
noiseless_c.add(gates.Z(4))
if np.random.random() < p0:
noiseless_c.add(gates.Collapse(4))
if np.random.random() < p1:
noiseless_c.add(gates.Collapse(4))
noiseless_c.add(gates.X(4))
target_state.append(noiseless_c(np.copy(initial_state)))
np.testing.assert_allclose(final_state, target_state)
qibo.set_backend(original_backend)
def test_thermal_relaxation_channel_errors(backend, t1, t2, time, excpop):
with pytest.raises(ValueError):
gate = gates.ThermalRelaxationChannel(0,
t1,
t2,
time,
excited_population=excpop)
def test_thermal_relaxation_channel_repeated(backend):
initial_state = random_state(5)
c = Circuit(5)
c.add(
gates.ThermalRelaxationChannel(4,
t1=1.0,
t2=0.6,
time=0.8,
excited_population=0.8,
seed=123))
final_state = c(K.cast(np.copy(initial_state)), nshots=30)
pz, p0, p1 = c.queue[0].calculate_probabilities(1.0, 0.6, 0.8, 0.8)
np.random.seed(123)
target_state = []
collapse = gates.M(4, collapse=True)
collapse.nqubits = 5
zgate, xgate = gates.Z(4), gates.X(4)
for _ in range(30):
state = K.cast(np.copy(initial_state))
if np.random.random() < pz:
state = zgate(state)
if np.random.random() < p0:
state = K.state_vector_collapse(collapse, state, [0])
if np.random.random() < p1:
state = K.state_vector_collapse(collapse, state, [0])
state = xgate(state)
target_state.append(K.copy(state))
target_state = K.stack(target_state)
K.assert_allclose(final_state, target_state)
def test_thermal_relaxation_channel_errors(backend, t1, t2, time, excpop):
original_backend = qibo.get_backend()
qibo.set_backend(backend)
with pytest.raises(ValueError):
gate = gates.ThermalRelaxationChannel(0,
t1,
t2,
time,
excited_population=excpop)
qibo.set_backend(original_backend)
def test_thermal_relaxation_channel(backend, t1, t2, time, excpop):
"""Check ``gates.ThermalRelaxationChannel`` on a 3-qubit random density matrix."""
original_backend = qibo.get_backend()
qibo.set_backend(backend)
initial_rho = utils.random_density_matrix(3)
c = models.Circuit(3, density_matrix=True)
gate = gates.ThermalRelaxationChannel(0,
t1,
t2,
time=time,
excited_population=excpop)
c.add(gate)
final_rho = c(np.copy(initial_rho))
exp, p0, p1 = gates.ThermalRelaxationChannel._calculate_probs(
t1, t2, time, excpop)
if t2 > t1:
matrix = np.diag([1 - p1, p0, p1, 1 - p0])
matrix[0, -1], matrix[-1, 0] = exp, exp
matrix = matrix.reshape(4 * (2, ))
# Apply matrix using Eq. (3.28) from arXiv:1111.6950
target_rho = np.copy(initial_rho).reshape(6 * (2, ))
target_rho = np.einsum("abcd,aJKcjk->bJKdjk", matrix, target_rho)
target_rho = target_rho.reshape(initial_rho.shape)
else:
pz = exp
pi = 1 - pz - p0 - p1
dtype = initial_rho.dtype
collapsed_rho = np.copy(initial_rho).reshape(6 * (2, ))
collapsed_rho[0, :, :, 1, :, :] = np.zeros(4 * (2, ), dtype=dtype)
collapsed_rho[1, :, :, 0, :, :] = np.zeros(4 * (2, ), dtype=dtype)
collapsed_rho[1, :, :, 1, :, :] = np.zeros(4 * (2, ), dtype=dtype)
collapsed_rho = collapsed_rho.reshape((8, 8))
collapsed_rho /= np.trace(collapsed_rho)
mx = np.kron(np.array([[0, 1], [1, 0]]), np.eye(4))
mz = np.kron(np.array([[1, 0], [0, -1]]), np.eye(4))
z_rho = mz.dot(initial_rho.dot(mz))
flipped_rho = mx.dot(collapsed_rho.dot(mx))
target_rho = (pi * initial_rho + pz * z_rho + p0 * collapsed_rho +
p1 * flipped_rho)
np.testing.assert_allclose(final_rho, target_rho)
# Try to apply to state vector if t1 < t2
if t1 < t2:
with pytest.raises(ValueError):
gate.state_vector_call(initial_rho) # pylint: disable=no-member
qibo.set_backend(original_backend)
