def test_crx_decomposition_correctness(self, phi, tol):
"""Test that the decomposition of the controlled X
qubit rotation is correct"""
expected = CRotx(phi)
obtained = np.kron(I, Rotz(-np.pi / 2)) @ CNOT @ np.kron(
I, Roty(-phi / 2)) @ CNOT @ np.kron(I, Roty(phi / 2)) @ np.kron(
I, Rotz(np.pi / 2))
assert np.allclose(expected, obtained, atol=tol, rtol=0)
def test_pauliz_tensor_hadamard(self, theta, phi, varphi, tol_stochastic):
"""Test that a tensor product involving PauliZ and hadamard works correctly"""
dev = qml.device("default.qubit", wires=3, shots=int(1e6))
@qml.qnode(dev, diff_method="parameter-shift")
def circuit(a, b, c):
ansatz(a, b, c)
return sample(qml.PauliZ(0) @ qml.Hadamard(1) @ qml.PauliY(2))
s1 = circuit(theta, phi, varphi)
zero_state = np.zeros(2**3)
zero_state[0] = 1
psi = zero_state
psi = tensor_product([Rotx(theta), I, I]) @ zero_state
psi = tensor_product([I, Rotx(phi), I]) @ psi
psi = tensor_product([I, I, Rotx(varphi)]) @ psi
psi = tensor_product([CNOT, I]) @ psi
psi = tensor_product([I, CNOT]) @ psi
# Diagonalize according to the observable
psi = tensor_product([I, Roty(-np.pi / 4), I]) @ psi
psi = tensor_product([I, I, Z]) @ psi
psi = tensor_product([I, I, S]) @ psi
psi = tensor_product([I, I, H]) @ psi
expected_probabilities = np.abs(psi)**2
assert np.allclose(dev.probability(),
expected_probabilities,
atol=tol_stochastic,
rtol=0)
# s1 should only contain 1 and -1
assert np.allclose(s1**2, 1, atol=tol_stochastic, rtol=0)
def test_multiple_expectation_different_wires(self, qubit_device_2_wires,
tol):
"""Tests that qnodes return multiple expectation values."""
a, b, c = torch.tensor(0.5), torch.tensor(0.54), torch.tensor(0.3)
@qml.qnode(qubit_device_2_wires, interface='torch')
def circuit(x, y, z):
qml.RX(x, wires=[0])
qml.RZ(y, wires=[0])
qml.CNOT(wires=[0, 1])
qml.RY(y, wires=[0])
qml.RX(z, wires=[0])
return qml.expval(qml.PauliY(0)), qml.expval(qml.PauliZ(1))
res = circuit(a, b, c)
out_state = np.kron(Rotx(c.numpy()), I) @ np.kron(Roty(b.numpy()), I) @ CNOT \
@ np.kron(Rotz(b.numpy()), I) @ np.kron(Rotx(a.numpy()), I) @ np.array([1, 0, 0, 0])
ex0 = np.vdot(out_state, np.kron(Y, I) @ out_state)
ex1 = np.vdot(out_state, np.kron(I, Z) @ out_state)
ex = np.array([ex0, ex1])
assert np.allclose(ex, res.numpy(), atol=tol, rtol=0)