def test_invalid_qubit_state_vector(self):
"""Test that an exception is raised if the state
vector is the wrong size"""
dev = TensorNetworkTF(wires=2)
state = np.array([0, 123.432])
with pytest.raises(ValueError, match=r"State vector must be of length 2\*\*wires"):
dev.execute([qml.QubitStateVector(state, wires=[0])], [], {})
def test_qubit_state_vector(self, init_state, tol):
"""Test qubit state vector application"""
dev = TensorNetworkTF(wires=1)
state = init_state(1)
dev.execute([qml.QubitStateVector(state, wires=[0])], [], {})
res = dev._state.numpy().flatten()
expected = state
assert np.allclose(res, expected, atol=tol, rtol=0)
def test_two_qubit_parameters(self, init_state, op, func, theta, tol):
"""Test two qubit parametrized operations"""
dev = TensorNetworkTF(wires=2)
state = init_state(2)
queue = [qml.QubitStateVector(state, wires=[0, 1])]
queue += [op(theta, wires=[0, 1])]
dev.execute(queue, [], {})
res = dev._state.numpy().flatten()
expected = func(theta) @ state
assert np.allclose(res, expected, atol=tol, rtol=0)
def test_three_qubit_no_parameters(self, init_state, op, mat, tol):
"""Test non-parametrized three qubit operations"""
dev = TensorNetworkTF(wires=3)
state = init_state(3)
queue = [qml.QubitStateVector(state, wires=[0, 1, 2])]
queue += [op(wires=[0, 1, 2])]
dev.execute(queue, [], {})
res = dev._state.numpy().flatten()
expected = mat @ state
assert np.allclose(res, expected, atol=tol, rtol=0)
def test_basis_state(self, tol):
"""Test basis state initialization"""
dev = TensorNetworkTF(wires=4)
state = np.array([0, 0, 1, 0])
dev.execute([qml.BasisState(state, wires=[0, 1, 2, 3])], [], {})
res = dev._state.numpy().flatten()
expected = np.zeros([2 ** 4])
expected[np.ravel_multi_index(state, [2] * 4)] = 1
assert np.allclose(res, expected, atol=tol, rtol=0)
def test_qubit_unitary(self, init_state, mat, tol):
"""Test application of arbitrary qubit unitaries"""
N = int(np.log2(len(mat)))
dev = TensorNetworkTF(wires=N)
state = init_state(N)
queue = [qml.QubitStateVector(state, wires=range(N))]
queue += [qml.QubitUnitary(mat, wires=range(N))]
dev.execute(queue, [], {})
res = dev._state.numpy().flatten()
expected = mat @ state
assert np.allclose(res, expected, atol=tol, rtol=0)
def test_multi_mode_hermitian_expectation(self, theta, phi, tol):
"""Test that arbitrary multi-mode Hermitian expectation values are correct"""
A = np.array(
[
[-6, 2 + 1j, -3, -5 + 2j],
[2 - 1j, 0, 2 - 1j, -5 + 4j],
[-3, 2 + 1j, 0, -4 + 3j],
[-5 - 2j, -5 - 4j, -4 - 3j, -6],
]
)
dev = TensorNetworkTF(wires=2)
queue = [qml.RY(theta, wires=0), qml.RY(phi, wires=1), qml.CNOT(wires=[0, 1])]
observables = [qml.Hermitian(A, wires=[0, 1])]
for i in range(len(observables)):
observables[i].return_type = qml.operation.Expectation
res = dev.execute(queue, observables, {})
# below is the analytic expectation value for this circuit with arbitrary
# Hermitian observable A
expected = 0.5 * (
6 * np.cos(theta) * np.sin(phi)
- np.sin(theta) * (8 * np.sin(phi) + 7 * np.cos(phi) + 3)
- 2 * np.sin(phi)
- 6 * np.cos(phi)
- 6
)
assert np.allclose(res, expected, atol=tol, rtol=0)
def test_rotation(self, init_state, tol):
"""Test three axis rotation gate"""
dev = TensorNetworkTF(wires=1)
state = init_state(1)
a = 0.542
b = 1.3432
c = -0.654
queue = [qml.QubitStateVector(state, wires=[0])]
queue += [qml.Rot(a, b, c, wires=0)]
dev.execute(queue, [], {})
res = dev._state.numpy().flatten()
expected = rot(a, b, c) @ state
assert np.allclose(res, expected, atol=tol, rtol=0)
def test_hermitian_expectation(self, theta, phi, tol):
"""Test that arbitrary Hermitian expectation values are correct"""
dev = TensorNetworkTF(wires=2)
queue = [
qml.RY(theta, wires=0),
qml.RY(phi, wires=1),
qml.CNOT(wires=[0, 1])
]
observables = [qml.Hermitian(A, wires=[i]) for i in range(2)]
for i in range(len(observables)):
observables[i].return_type = qml.operation.Expectation
res = dev.execute(queue, observables, {})
a = A[0, 0]
re_b = A[0, 1].real
d = A[1, 1]
ev1 = ((a - d) * np.cos(theta) +
2 * re_b * np.sin(theta) * np.sin(phi) + a + d) / 2
ev2 = ((a - d) * np.cos(theta) * np.cos(phi) + 2 * re_b * np.sin(phi) +
a + d) / 2
expected = np.array([ev1, ev2])
assert np.allclose(res, expected, atol=tol, rtol=0)
def test_single_wire_expectation(self, gate, obs, expected, theta, phi, tol):
"""Test that identity expectation value (i.e. the trace) is 1"""
dev = TensorNetworkTF(wires=2)
queue = [gate(theta, wires=0), gate(phi, wires=1), qml.CNOT(wires=[0, 1])]
observables = [obs(wires=[i]) for i in range(2)]
for i in range(len(observables)):
observables[i].return_type = qml.operation.Expectation
res = dev.execute(queue, observables, {})
assert np.allclose(res, expected(theta, phi), atol=tol, rtol=0)
def test_var(self, theta, phi, tol):
"""Tests for variance calculation"""
dev = TensorNetworkTF(wires=1)
# test correct variance for <Z> of a rotated state
queue = [qml.RX(phi, wires=0), qml.RY(theta, wires=0)]
observables = [qml.PauliZ(wires=[0])]
for i in range(len(observables)):
observables[i].return_type = qml.operation.Variance
res = dev.execute(queue, observables, {})
expected = 0.25 * (3 - np.cos(2 * theta) - 2 * np.cos(theta) ** 2 * np.cos(2 * phi))
assert np.allclose(res, expected, atol=tol, rtol=0)
def test_var_hermitian(self, theta, phi, tol):
"""Tests for variance calculation using an arbitrary Hermitian observable"""
dev = TensorNetworkTF(wires=2)
# test correct variance for <H> of a rotated state
H = np.array([[4, -1 + 6j], [-1 - 6j, 2]])
queue = [qml.RX(phi, wires=0), qml.RY(theta, wires=0)]
observables = [qml.Hermitian(H, wires=[0])]
for i in range(len(observables)):
observables[i].return_type = qml.operation.Variance
res = dev.execute(queue, observables, {})
expected = 0.5 * (2 * np.sin(2 * theta) * np.cos(phi)**2 +
24 * np.sin(phi) * np.cos(phi) *
(np.sin(theta) - np.cos(theta)) +
35 * np.cos(2 * phi) + 39)
assert np.allclose(res, expected, atol=tol, rtol=0)