def test_generate_germs_with_candidate_germ_counts(self):
germs = germsel.find_germs(self.mdl_target_noisy,
randomize=False,
candidate_germ_counts={
3: 'all upto',
4: 10,
5: 10,
6: 10
})
def test_build_up_breadth(self):
germs = germsel.find_germs_breadthfirst(self.neighbors, self.germ_set,
**self.options)
# TODO assert correctness
algorithm_kwargs = dict(germs_list=self.germ_set, **self.options)
germs_driver = germsel.find_germs(self.mdl_target_noisy,
randomize=False,
algorithm='greedy',
algorithm_kwargs=algorithm_kwargs)
def test_grasp_germ_set_optimization(self):
soln = germsel.find_germs_grasp(self.neighbors,
self.germ_set,
alpha=0.1,
**self.options)
# TODO assert correctness
best, initial, local = germsel.find_germs_grasp(self.neighbors,
self.germ_set,
alpha=0.1,
return_all=True,
**self.options)
# TODO shouldn't this pass?
# self.assertEqual(soln, best)
algorithm_kwargs = dict(germs_list=self.germ_set, **self.options)
soln_driver = germsel.find_germs(self.mdl_target_noisy,
randomize=False,
algorithm='grasp',
algorithm_kwargs=algorithm_kwargs)
def test_optimize_integer_germs_slack_with_fixed_slack(self):
finalGerms = germsel.find_germs_integer_slack(self.mdl_target_noisy,
self.germ_set,
fixed_slack=0.1,
verbosity=4)
# TODO assert correctness
finalGerms_all, weights, scores = germsel.find_germs_integer_slack(
self.mdl_target_noisy,
self.germ_set,
fixed_slack=0.1,
return_all=True,
verbosity=4)
self.assertEqual(finalGerms, finalGerms_all)
algorithm_kwargs = dict(germs_list=self.germ_set, fixed_slack=0.1)
finalGerms_driver = germsel.find_germs(
self.mdl_target_noisy,
randomize=False,
algorithm='slack',
algorithm_kwargs=algorithm_kwargs,
verbosity=4)
self.assertEqual(finalGerms_driver, finalGerms)
def test_generate_germs_raises_on_bad_algorithm(self):
with self.assertRaises(ValueError):
germsel.find_germs(self.mdl_target_noisy, algorithm='foobar')
def test_auto_experiment_design(self):
# Let's construct a 1-qubit $X(\pi/2)$, $Y(\pi/2)$, $I$ model for which we will need to find germs and fiducials.
target_model = mc.create_explicit_model_from_expressions(
[('Q0', )], ['Gi', 'Gx', 'Gy'],
["I(Q0)", "X(pi/2,Q0)", "Y(pi/2,Q0)"])
# ## Hands-off
# We begin by demonstrating the most hands-off approach.
# We can generate a germ set simply by providing the target model. (and seed so it's deterministic)
germs = germsel.find_germs(target_model, seed=2017)
# In the same way we can generate preparation and measurement fiducials.
prepFiducials, measFiducials = fidsel.find_fiducials(target_model)
#test return_all - this just prints more info...
p, m = fidsel.find_fiducials(target_model,
algorithm_kwargs={'return_all': True})
#test invalid algorithm
with self.assertRaises(ValueError):
fidsel.find_fiducials(target_model, algorithm='foobar')
# Now that we have germs and fiducials, we can construct the list of experiments we need to perform in
# order to do GST. The only new things to provide at this point are the sizes for the experiments we want
# to perform (in this case we want to perform between 0 and 256 gates between fiducial pairs, going up
# by a factor of 2 at each stage).
maxLengths = [0] + [2**n for n in range(8 + 1)]
listOfExperiments = gstcircuits.create_lsgst_circuits(
target_model.operations.keys(), prepFiducials, measFiducials,
germs, maxLengths)
# The list of `Circuit` that the previous function gave us isn't necessarily the most readable
# form to present the information in, so we can write the experiment list out to an empty data
# file to be filled in after the experiments are performed.
graspGerms = germsel.find_germs(target_model,
algorithm='grasp',
seed=2017,
num_gs_copies=2,
candidate_germ_counts={
3: 'all upto',
4: 10,
5: 10,
6: 10
},
candidate_seed=2017,
algorithm_kwargs={'iterations': 1})
slackPrepFids, slackMeasFids = fidsel.find_fiducials(
target_model,
algorithm='slack',
algorithm_kwargs={'slack_frac': 0.25})
fidsel.find_fiducials(
target_model, algorithm='slack'
) # slacFrac == 1.0 if don't specify either slack_frac or fixed_slack
germsMaxLength3 = germsel.find_germs(
target_model, candidate_germ_counts={3: 'all upto'}, seed=2017)
uniformPrepFids, uniformMeasFids = fidsel.find_fiducials(
target_model,
max_fid_length=3,
algorithm='grasp',
algorithm_kwargs={'iterations': 100})
incompletePrepFids, incompleteMeasFids = fidsel.find_fiducials(
target_model, max_fid_length=1)
nonSingletonGerms = germsel.find_germs(
target_model,
num_gs_copies=2,
force=None,
candidate_germ_counts={4: 'all upto'},
algorithm='grasp',
algorithm_kwargs={'iterations': 5},
seed=2017)
omitIdentityPrepFids, omitIdentityMeasFids = fidsel.find_fiducials(
target_model, omit_identity=False, ops_to_omit=['Gi'])