def test_coherent_noise(self):
"""
Test for pulse genration with coherent noise.
"""
coeff = np.array([0.1, 0.2, 0.3, 0.4])
tlist = np.array([0., 1., 2., 3.])
ham = sigmaz()
pulse1 = Pulse(ham, 1, tlist, coeff)
# Add coherent noise with the same tlist
pulse1.add_coherent_noise(sigmay(), 0, tlist, coeff)
assert_allclose(
pulse1.get_ideal_qobjevo(2)(0).full(),
tensor(identity(2), sigmaz()).full() * 0.1)
assert_(len(pulse1.coherent_noise) == 1)
noise_qu, c_ops = pulse1.get_noisy_qobjevo(2)
assert_allclose(c_ops, [])
assert_allclose(pulse1.get_full_tlist(), np.array([0., 1., 2., 3.]))
def test_noisy_pulse(self):
"""
Test for lindblad noise and different tlist
"""
coeff = np.array([0.1, 0.2, 0.3, 0.4])
tlist = np.array([0., 1., 2., 3.])
ham = sigmaz()
pulse1 = Pulse(ham, 1, tlist, coeff)
# Add coherent noise and lindblad noise with different tlist
pulse1.spline_kind = "step_func"
tlist_noise = np.array([0., 1., 2.5, 3.])
coeff_noise = np.array([0., 0.5, 0.1, 0.5])
pulse1.add_coherent_noise(sigmay(), 0, tlist_noise, coeff_noise)
tlist_noise2 = np.array([0., 0.5, 2, 3.])
coeff_noise2 = np.array([0., 0.1, 0.2, 0.3])
pulse1.add_lindblad_noise(sigmax(), 1, coeff=True)
pulse1.add_lindblad_noise(sigmax(),
0,
tlist=tlist_noise2,
coeff=coeff_noise2)
assert_allclose(
pulse1.get_ideal_qobjevo(2)(0).full(),
tensor(identity(2), sigmaz()).full() * 0.1)
noise_qu, c_ops = pulse1.get_noisy_qobjevo(2)
assert_allclose(pulse1.get_full_tlist(),
np.array([0., 0.5, 1., 2., 2.5, 3.]))
if parse_version(qutip.__version__) >= parse_version('5.dev'):
expected = QobjEvo([[
tensor(identity(2), sigmaz()),
np.array([0.1, 0.1, 0.2, 0.3, 0.3, 0.4])
],
[
tensor(sigmay(), identity(2)),
np.array([0., 0., 0.5, 0.5, 0.1, 0.5])
]],
tlist=np.array([0., 0.5, 1., 2., 2.5, 3.]),
order=0)
else:
expected = QobjEvo([[
tensor(identity(2), sigmaz()),
np.array([0.1, 0.1, 0.2, 0.3, 0.3, 0.4])
],
[
tensor(sigmay(), identity(2)),
np.array([0., 0., 0.5, 0.5, 0.1, 0.5])
]],
tlist=np.array([0., 0.5, 1., 2., 2.5, 3.]),
args={"_step_func_coeff": True})
_compare_qobjevo(noise_qu, expected, 0, 3)
for c_op in c_ops:
try:
isconstant = c_op.isconstant
except AttributeError:
isconstant = (len(c_op.ops) == 0)
if isconstant:
assert_allclose(
c_op(0).full(),
tensor(identity(2), sigmax()).full())
else:
if parse_version(qutip.__version__) >= parse_version('5.dev'):
expected = QobjEvo([
tensor(sigmax(), identity(2)),
np.array([0., 0.1, 0.1, 0.2, 0.2, 0.3])
],
tlist=np.array(
[0., 0.5, 1., 2., 2.5, 3.]),
order=0)
else:
expected = QobjEvo([
tensor(sigmax(), identity(2)),
np.array([0., 0.1, 0.1, 0.2, 0.2, 0.3])
],
tlist=np.array(
[0., 0.5, 1., 2., 2.5, 3.]),
args={"_step_func_coeff": True})
_compare_qobjevo(c_op, expected, 0, 3)