def test_decoherence_noise(self):
"""
Test for the decoherence noise
"""
tlist = np.array([1, 2, 3, 4, 5, 6])
coeff = np.array([1, 1, 1, 1, 1, 1])
# Time-dependent
decnoise = DecoherenceNoise(
sigmaz(), coeff=coeff, tlist=tlist, targets=[1])
dims = [2] * 2
pulses, systematic_noise = decnoise.get_noisy_dynamics(dims=dims)
noisy_qu, c_ops = systematic_noise.get_noisy_qobjevo(dims=dims)
assert_allclose(c_ops[0].ops[0].qobj, tensor(qeye(2), sigmaz()))
assert_allclose(c_ops[0].ops[0].coeff, coeff)
assert_allclose(c_ops[0].tlist, tlist)
# Time-indenpendent and all qubits
decnoise = DecoherenceNoise(sigmax(), all_qubits=True)
pulses, systematic_noise = decnoise.get_noisy_dynamics(dims=dims)
noisy_qu, c_ops = systematic_noise.get_noisy_qobjevo(dims=dims)
c_ops = [qu.cte for qu in c_ops]
assert_(tensor([qeye(2), sigmax()]) in c_ops)
assert_(tensor([sigmax(), qeye(2)]) in c_ops)
# Time-denpendent and all qubits
decnoise = DecoherenceNoise(
sigmax(), all_qubits=True, coeff=coeff*2, tlist=tlist)
pulses, systematic_noise = decnoise.get_noisy_dynamics(dims=dims)
noisy_qu, c_ops = systematic_noise.get_noisy_qobjevo(dims=dims)
assert_allclose(c_ops[0].ops[0].qobj, tensor(sigmax(), qeye(2)))
assert_allclose(c_ops[0].ops[0].coeff, coeff*2)
assert_allclose(c_ops[0].tlist, tlist)
assert_allclose(c_ops[1].ops[0].qobj, tensor(qeye(2), sigmax()))
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, label="sx")
proc.set_all_coeffs({"sx": np.array([1.])})
proc.set_all_tlist(tlist)
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.model._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_decoherence_noise(self):
"""
Test for the decoherence noise
"""
tlist = np.array([0, 1, 2, 3, 4, 5, 6])
coeff = np.array([1, 1, 1, 1, 1, 1, 1])
# Time-dependent
decnoise = DecoherenceNoise(sigmaz(),
coeff=coeff,
tlist=tlist,
targets=[1])
dims = [2] * 2
systematic_noise = Pulse(None,
None,
label="systematic_noise",
spline_kind="step_func")
pulses, systematic_noise = decnoise.get_noisy_pulses(
systematic_noise=systematic_noise, dims=dims)
noisy_qu, c_ops = systematic_noise.get_noisy_qobjevo(dims=dims)
assert_allclose(c_ops[0](0).full(), tensor(qeye(2), sigmaz()).full())
# Time-independent and all qubits
decnoise = DecoherenceNoise(sigmax(), all_qubits=True)
pulses, systematic_noise = decnoise.get_noisy_pulses(dims=dims)
noisy_qu, c_ops = systematic_noise.get_noisy_qobjevo(dims=dims)
c_ops = [qu(0) for qu in c_ops]
assert_(tensor([qeye(2), sigmax()]) in c_ops)
assert_(tensor([sigmax(), qeye(2)]) in c_ops)
# Time-denpendent and all qubits
decnoise = DecoherenceNoise(sigmax(),
all_qubits=True,
coeff=coeff * 2,
tlist=tlist)
systematic_noise = Pulse(None,
None,
label="systematic_noise",
spline_kind="step_func")
pulses, systematic_noise = decnoise.get_noisy_pulses(
systematic_noise=systematic_noise, dims=dims)
noisy_qu, c_ops = systematic_noise.get_noisy_qobjevo(dims=dims)
assert_allclose(c_ops[0](0).full(),
tensor(sigmax(), qeye(2)).full() * 2)
assert_allclose(c_ops[1](0).full(),
tensor(qeye(2), sigmax()).full() * 2)
def testGetObjevo(self):
tlist = np.array([1, 2, 3, 4, 5, 6], dtype=float)
coeff = np.array([1, 1, 1, 1, 1, 1], dtype=float)
processor = Processor(N=1)
processor.add_control(sigmaz())
processor.pulses[0].tlist = tlist
processor.pulses[0].coeff = coeff
# without noise
unitary_qobjevo, _ = processor.get_qobjevo(
args={"test": True}, noisy=False)
assert_allclose(unitary_qobjevo.ops[0].qobj, sigmaz())
assert_allclose(unitary_qobjevo.tlist, tlist)
assert_allclose(unitary_qobjevo.ops[0].coeff, coeff[0])
assert_(unitary_qobjevo.args["test"],
msg="Arguments not correctly passed on")
# with decoherence noise
dec_noise = DecoherenceNoise(
c_ops=sigmax(), coeff=coeff, tlist=tlist)
processor.add_noise(dec_noise)
assert_equal(unitary_qobjevo.to_list(),
processor.get_qobjevo(noisy=False)[0].to_list())
noisy_qobjevo, c_ops = processor.get_qobjevo(
args={"test": True}, noisy=True)
assert_(noisy_qobjevo.args["_step_func_coeff"],
msg="Spline type not correctly passed on")
assert_(noisy_qobjevo.args["test"],
msg="Arguments not correctly passed on")
assert_(sigmaz() in [pair[0] for pair in noisy_qobjevo.to_list()])
assert_equal(c_ops[0].ops[0].qobj, sigmax())
assert_equal(c_ops[0].tlist, tlist)
# with amplitude noise
processor = Processor(N=1, spline_kind="cubic")
processor.add_control(sigmaz())
tlist = np.linspace(1, 6, int(5/0.2))
coeff = np.random.rand(len(tlist))
processor.pulses[0].tlist = tlist
processor.pulses[0].coeff = coeff
amp_noise = ControlAmpNoise(coeff=coeff, tlist=tlist)
processor.add_noise(amp_noise)
noisy_qobjevo, c_ops = processor.get_qobjevo(
args={"test": True}, noisy=True)
assert_(not noisy_qobjevo.args["_step_func_coeff"],
msg="Spline type not correctly passed on")
assert_(noisy_qobjevo.args["test"],
msg="Arguments not correctly passed on")
assert_equal(len(noisy_qobjevo.ops), 2)
assert_equal(sigmaz(), noisy_qobjevo.ops[0].qobj)
assert_allclose(coeff, noisy_qobjevo.ops[0].coeff, rtol=1.e-10)
def test_collapse_with_different_tlist(self):
"""
Test if there are errors raised because of wrong tlist handling.
"""
qc = QubitCircuit(1)
qc.add_gate("X", 0)
proc = LinearSpinChain(1)
proc.load_circuit(qc)
tlist = np.linspace(0, 30., 100)
coeff = tlist * 0.1
noise = DecoherenceNoise(sigmam(), targets=0, coeff=coeff, tlist=tlist)
proc.add_noise(noise)
proc.run_state(basis(2, 0))