def TestNoise(self):
"""
Test for Processor with noise
"""
# setup and fidelity without noise
init_state = qubit_states(2, [0, 0, 0, 0])
tlist = np.array([0., np.pi/2.])
a = destroy(2)
proc = Processor(N=2)
proc.add_control(sigmax(), targets=1)
proc.pulses[0].tlist = tlist
proc.pulses[0].coeff = np.array([1])
result = proc.run_state(init_state=init_state)
assert_allclose(
fidelity(result.states[-1], qubit_states(2, [0, 1, 0, 0])),
1, rtol=1.e-7)
# decoherence noise
dec_noise = DecoherenceNoise([0.25*a], targets=1)
proc.add_noise(dec_noise)
result = proc.run_state(init_state=init_state)
assert_allclose(
fidelity(result.states[-1], qubit_states(2, [0, 1, 0, 0])),
0.981852, rtol=1.e-3)
# white random noise
proc.noise = []
white_noise = RandomNoise(0.2, np.random.normal, loc=0.1, scale=0.1)
proc.add_noise(white_noise)
result = proc.run_state(init_state=init_state)
def test_random_noise(self):
"""
Test for the white noise
"""
tlist = np.array([1, 2, 3, 4, 5, 6])
coeff = np.array([1, 1, 1, 1, 1, 1])
dummy_qobjevo = QobjEvo(sigmaz(), tlist=tlist)
mean = 0.
std = 0.5
pulses = [
Pulse(sigmaz(), 0, tlist, coeff),
Pulse(sigmax(), 0, tlist, coeff * 2),
Pulse(sigmay(), 0, tlist, coeff * 3)
]
# random noise with operators from proc_qobjevo
gaussnoise = RandomNoise(dt=0.1,
rand_gen=np.random.normal,
loc=mean,
scale=std)
noisy_pulses, systematic_noise = \
gaussnoise.get_noisy_dynamics(pulses=pulses)
assert_allclose(noisy_pulses[2].qobj, sigmay())
assert_allclose(noisy_pulses[1].coherent_noise[0].qobj, sigmax())
assert_allclose(len(noisy_pulses[0].coherent_noise[0].tlist),
len(noisy_pulses[0].coherent_noise[0].coeff))
# random noise with dt and other random number generator
pulses = [
Pulse(sigmaz(), 0, tlist, coeff),
Pulse(sigmax(), 0, tlist, coeff * 2),
Pulse(sigmay(), 0, tlist, coeff * 3)
]
gaussnoise = RandomNoise(lam=0.1, dt=0.2, rand_gen=np.random.poisson)
assert_(gaussnoise.rand_gen is np.random.poisson)
noisy_pulses, systematic_noise = \
gaussnoise.get_noisy_dynamics(pulses=pulses)
assert_allclose(noisy_pulses[0].coherent_noise[0].tlist,
np.linspace(1, 6,
int(5 / 0.2) + 1))
assert_allclose(noisy_pulses[1].coherent_noise[0].tlist,
np.linspace(1, 6,
int(5 / 0.2) + 1))
assert_allclose(noisy_pulses[2].coherent_noise[0].tlist,
np.linspace(1, 6,
int(5 / 0.2) + 1))
import matplotlib.pyplot as plt
from qutip import sigmaz, sigmay
from qutip.qip.device import Processor
from qutip.qip.noise import RandomNoise
# add control Hamiltonians
processor = Processor(N=1)
processor.add_control(sigmaz(), targets=0)
# define pulse coefficients and tlist for all pulses
processor.pulses[0].coeff = np.array([0.3, 0.5, 0.])
processor.set_all_tlist(
np.array([0., np.pi / 2., 2 * np.pi / 2, 3 * np.pi / 2]))
# define noise, loc and scale are keyword arguments for np.random.normal
gaussnoise = RandomNoise(dt=0.01,
rand_gen=np.random.normal,
loc=0.00,
scale=0.02)
processor.add_noise(gaussnoise)
# Plot the ideal pulse
fig1, axis1 = processor.plot_pulses(title="Original control amplitude",
figsize=(5, 3))
# Plot the noisy pulse
qobjevo, _ = processor.get_qobjevo(noisy=True)
noisy_coeff = qobjevo.to_list()[1][1] + qobjevo.to_list()[2][1]
fig2, axis2 = processor.plot_pulses(title="Noisy control amplitude",
figsize=(5, 3))
axis2[0].step(qobjevo.tlist, noisy_coeff)