def test_tempo_bad_input():
start_time = -0.3
end_time = 0.84
correlation_function = lambda t: (np.cos(6.0*t)+1j*np.sin(6.0*t)) \
* np.exp(-12.0*t)
correlations = tempo.CustomCorrelations(correlation_function,
max_correlation_time=0.5)
bath = tempo.Bath(0.5 * tempo.operators.sigma("z"), correlations)
tempo_param = tempo.PtTempoParameters(0.1, 5, 1.0e-5, name="rough-A")
tempo.PtTempo(bath=bath,
parameters=tempo_param,
start_time=start_time,
end_time=end_time)
with pytest.raises(AssertionError):
tempo.PtTempo(bath=bath,
parameters=tempo_param,
start_time="bla",
end_time=end_time)
with pytest.raises(AssertionError):
tempo.PtTempo(bath=bath,
parameters=tempo_param,
start_time=start_time,
end_time="bla")
with pytest.raises(AssertionError):
tempo.PtTempo(bath=bath,
parameters=tempo_param,
start_time=0.0,
end_time=0.0001)
def test_tempo_bad_input():
start_time = -0.3
end_time = 0.84
system = tempo.System(0.5 * tempo.operators.sigma("x"))
correlation_function = lambda t: (np.cos(6.0*t)+1j*np.sin(6.0*t)) \
* np.exp(-12.0*t)
correlations = tempo.CustomCorrelations(correlation_function,
max_correlation_time=0.5)
bath = tempo.Bath(0.5 * tempo.operators.sigma("z"), correlations)
initial_state = tempo.operators.spin_dm("z+")
tempo_param_A = tempo.TempoParameters(0.1, 5, 1.0e-5, name="rough-A")
with pytest.raises(AssertionError):
tempo_sys_A = tempo.Tempo(system=system,
bath=bath,
parameters=tempo_param_A,
initial_state="bla",
start_time=start_time)
with pytest.raises(AssertionError):
tempo_sys_A = tempo.Tempo(system=system,
bath=bath,
parameters=tempo_param_A,
initial_state=initial_state,
start_time="bla")
tempo_sys_A = tempo.Tempo(system=system,
bath=bath,
parameters=tempo_param_A,
initial_state=initial_state,
start_time=start_time)
with pytest.raises(AssertionError):
tempo_sys_A.compute(end_time="bla", progress_type="bar")
def test_pt_tempo():
start_time = -0.3
end_time = 0.84
system = tempo.System(0.5 * tempo.operators.sigma("x"))
correlation_function = lambda t: (np.cos(6.0*t)+1j*np.sin(6.0*t)) \
* np.exp(-12.0*t)
correlations = tempo.CustomCorrelations(correlation_function,
max_correlation_time=0.5)
bath = tempo.Bath(0.5 * tempo.operators.sigma("z"), correlations)
initial_state = tempo.operators.spin_dm("z+")
tempo_param_A = tempo.PtTempoParameters(0.1, 5, 1.0e-5, name="rough-A")
pt_tempo_sys_A = tempo.PtTempo(bath=bath,
parameters=tempo_param_A,
start_time=start_time,
end_time=end_time)
assert pt_tempo_sys_A.dimension == 2
pt_tempo_sys_A.compute()
pt_A = pt_tempo_sys_A.get_process_tensor()
assert len(pt_A.times) == 12
tempo_param_B = tempo.PtTempoParameters(0.1, None, 1.0e-5, name="rough-B")
pt_tempo_sys_B = tempo.PtTempo(bath=bath,
parameters=tempo_param_B,
start_time=start_time,
end_time=end_time)
pt_B = pt_tempo_sys_B.get_process_tensor()
def test_tempo():
start_time = -0.3
end_time1 = 0.4
end_time2 = 0.6
end_time3 = 0.84
system = tempo.System(0.5 * tempo.operators.sigma("x"))
correlation_function = lambda t: (np.cos(6.0*t)+1j*np.sin(6.0*t)) \
* np.exp(-12.0*t)
correlations = tempo.CustomCorrelations(correlation_function,
max_correlation_time=0.5)
bath = tempo.Bath(0.5 * tempo.operators.sigma("z"), correlations)
initial_state = tempo.operators.spin_dm("z+")
tempo_param_A = tempo.TempoParameters(0.1, 5, 1.0e-5, name="rough-A")
tempo_sys_A = tempo.Tempo(system=system,
bath=bath,
parameters=tempo_param_A,
initial_state=initial_state,
start_time=start_time)
assert tempo_sys_A.dimension == 2
tempo_sys_A.compute(end_time=end_time1, progress_type="bar")
tempo_sys_A.compute(end_time=end_time2, progress_type="silent")
tempo_sys_A.compute(end_time=end_time3, progress_type="simple")
dyn_A = tempo_sys_A.get_dynamics()
assert len(dyn_A.times) == 13
def test_plot_correlations_with_parameters():
correlation_function = lambda t: (np.cos(t) + 1j * np.sin(6.0 * t)
) * np.exp(-2.0 * t)
correlations = tempo.CustomCorrelations(correlation_function,
max_correlation_time=10.0)
param = tempo.TempoParameters(dt=0.1, dkmax=50, epsrel=3.9e-8)
tempo.helpers.plot_correlations_with_parameters(correlations, param)
def test_guess_pt_tempo_parameters():
correlation_function = lambda t: (np.cos(t) + 1j * np.sin(6.0 * t)
) * np.exp(-2.0 * t)
correlations = tempo.CustomCorrelations(correlation_function,
max_correlation_time=10.0)
bath = tempo.Bath(0.5 * tempo.operators.sigma("z"), correlations)
with pytest.warns(UserWarning):
param = tempo.guess_pt_tempo_parameters(bath=bath,
start_time=0.0,
end_time=15.0)
def test_tempo_compute():
start_time = -0.3
end_time = 0.84
correlation_function = lambda t: (np.cos(6.0*t)+1j*np.sin(6.0*t)) \
* np.exp(-12.0*t)
correlations = tempo.CustomCorrelations(correlation_function,
max_correlation_time=0.5)
bath = tempo.Bath(0.5 * tempo.operators.sigma("z"), correlations)
initial_state = tempo.operators.spin_dm("z+")
with pytest.warns(UserWarning):
pt_A = tempo.pt_tempo_compute(bath=bath,
start_time=start_time,
end_time=end_time)
def test_guess_tempo_parameters():
system = tempo.System(0.5 * tempo.operators.sigma("x"))
correlation_function = lambda t: (np.cos(t) + 1j * np.sin(6.0 * t)
) * np.exp(-2.0 * t)
correlations = tempo.CustomCorrelations(correlation_function,
max_correlation_time=10.0)
bath = tempo.Bath(0.5 * tempo.operators.sigma("z"), correlations)
with pytest.warns(UserWarning):
param = tempo.guess_tempo_parameters(bath=bath,
start_time=0.0,
end_time=15.0)
with pytest.raises(AssertionError): # bad start time input
param = tempo.guess_tempo_parameters(bath=bath,
start_time="bla",
end_time=15.0)
with pytest.raises(AssertionError): # bad end time input
param = tempo.guess_tempo_parameters(bath=bath,
start_time=0.0,
end_time="bla")
with pytest.raises(ValueError): # bad start/end time (swapped)
param = tempo.guess_tempo_parameters(bath=bath,
start_time=10.0,
end_time=0.0)
with pytest.raises(AssertionError): # bad tollerance
param = tempo.guess_tempo_parameters(bath=bath,
start_time=0.0,
end_time=15.0,
tollerance="bla")
with pytest.raises(AssertionError): # bad tollerance (negative)
param = tempo.guess_tempo_parameters(bath=bath,
start_time=0.0,
end_time=15.0,
tollerance=-0.2)
with pytest.warns(UserWarning): # reach MAX_DKMAX
param = tempo.guess_tempo_parameters(bath=bath,
start_time=0.0,
end_time=15.0,
tollerance=1.0e-12)