def test_complex128(highp):
tc.set_backend("tensorflow")
tc.set_dtype("complex128")
c = tc.Circuit(2)
c.H(1)
c.rx(0, theta=tc.gates.num_to_tensor(1j))
c.wavefunction()
assert np.allclose(c.expectation((tc.gates.z(), [1])), 0)
def test_wavefunction():
qc = tc.Circuit(2)
qc.apply_double_gate(
tc.gates.Gate(np.arange(16).reshape(2, 2, 2, 2).astype(np.complex64)),
0, 1)
assert np.real(qc.wavefunction()[0][2]) == 8
qc = tc.Circuit(2)
qc.apply_double_gate(
tc.gates.Gate(np.arange(16).reshape(2, 2, 2, 2).astype(np.complex64)),
1, 0)
qc.wavefunction()
assert np.real(qc.wavefunction()[0][2]) == 4
qc = tc.Circuit(2)
qc.apply_single_gate(
tc.gates.Gate(np.arange(4).reshape(2, 2).astype(np.complex64)), 0)
qc.wavefunction()
assert np.real(qc.wavefunction()[0][2]) == 2
def test_postselection(backend):
c = tc.Circuit(3)
c.H(1)
c.H(2)
c.mid_measurement(1, 1)
c.mid_measurement(2, 1)
s = c.wavefunction()[0]
assert round(np.real(s[3]), 1) == 0.5
def test_exp_gate():
c = tc.Circuit(2)
c.exp(
0,
1,
unitary=tc.gates.array_to_tensor(
np.array([[1.0, 0, 0, 0], [0, -1.0, 0, 0], [0, 0, -1, 0],
[0, 0, 0, 1]])),
theta=tc.gates.num_to_tensor(np.pi / 2),
)
assert np.allclose(c.wavefunction()[0, 0], -1j)
def test_any_inputs_state(backend):
c = tc.Circuit(2, inputs=tc.array_to_tensor(np.array([0.0, 0.0, 0.0, 1.0])))
c.X(0)
z0 = c.expectation((tc.gates.z(), [0]))
assert z0 == 1.0
c = tc.Circuit(2, inputs=tc.array_to_tensor(np.array([0.0, 0.0, 1.0, 0.0])))
c.X(0)
z0 = c.expectation((tc.gates.z(), [0]))
assert z0 == 1.0
c = tc.Circuit(2, inputs=tc.array_to_tensor(np.array([1.0, 0.0, 0.0, 0.0])))
c.X(0)
z0 = c.expectation((tc.gates.z(), [0]))
assert z0 == -1.0
c = tc.Circuit(
2,
inputs=tc.array_to_tensor(np.array([1 / np.sqrt(2), 0.0, 1 / np.sqrt(2), 0.0])),
)
c.X(0)
z0 = c.expectation((tc.gates.z(), [0]))
assert np.allclose(z0, 0.0, rtol=1e-6)
def test_expectation_between_two_states(backend):
zp = np.array([1.0, 0.0])
zd = np.array([0.0, 1.0])
assert tc.expectation((tc.gates.y(), [0]), ket=zp, bra=zd) == 1j
c = tc.Circuit(3)
c.H(0)
c.ry(1, theta=tc.num_to_tensor(0.8))
c.cnot(1, 2)
state = c.wavefunction()
x1z2 = [(tc.gates.x(), [0]), (tc.gates.z(), [1])]
e1 = c.expectation(*x1z2)
e2 = tc.expectation(*x1z2, ket=state, bra=state, normalization=True)
assert np.allclose(e2, e1)
c = tc.Circuit(3)
c.H(0)
c.ry(1, theta=tc.num_to_tensor(0.8 + 0.7j))
c.cnot(1, 2)
state = c.wavefunction()
x1z2 = [(tc.gates.x(), [0]), (tc.gates.z(), [1])]
e1 = c.expectation(*x1z2) / tc.backend.norm(state) ** 2
e2 = tc.expectation(*x1z2, ket=state, normalization=True)
assert np.allclose(e2, e1)
c = tc.Circuit(2)
c.X(1)
s1 = c.state()
c2 = tc.Circuit(2)
c2.X(0)
s2 = c2.state()
c3 = tc.Circuit(2)
c3.H(1)
s3 = c3.state()
x1x2 = [(tc.gates.x(), [0]), (tc.gates.x(), [1])]
e = tc.expectation(*x1x2, ket=s1, bra=s2)
assert np.allclose(e, 1.0)
e2 = tc.expectation(*x1x2, ket=s3, bra=s2)
assert np.allclose(e2, 1.0 / np.sqrt(2))
def forward(theta):
c = tc.Circuit(2)
c.R(0, theta=theta, alpha=0.5, phi=0.8)
return tc.backend.real(c.expectation((tc.gates.z(), [0])))
def test_expectation():
c = tc.Circuit(2)
c.H(0)
assert np.allclose(c.expectation((tc.gates.z(), [0])), 0, atol=1e-7)
def test_measure():
c = tc.Circuit(3)
c.H(0)
c.h(1)
c.toffoli(0, 1, 2)
assert c.measure(2)[0] in ["0", "1"]
def test_basics():
c = tc.Circuit(2)
c.x(0)
assert np.allclose(c.amplitude("10"), np.array(1.0))
c.CNOT(0, 1)
assert np.allclose(c.amplitude("11"), np.array(1.0))
def test_any_gate():
c = tc.Circuit(2)
c.any(0, unitary=np.eye(2))
assert np.allclose(c.expectation((tc.gates.z(), [0])), 1.0)
