def test_results_by_qubit_groups():
er1 = ExperimentResult(
setting=ExperimentSetting(plusX(0), sZ(0)),
expectation=0.0,
std_err=0.0,
total_counts=1,
)
er2 = ExperimentResult(
setting=ExperimentSetting(plusX(0), sZ(1)),
expectation=0.0,
std_err=0.0,
total_counts=1,
)
er3 = ExperimentResult(
setting=ExperimentSetting(plusX(0),
sX(0) * sZ(1)),
expectation=0.0,
std_err=0.0,
total_counts=1,
)
er4 = ExperimentResult(
setting=ExperimentSetting(plusX(0),
sX(0) * sZ(2)),
expectation=0.0,
std_err=0.0,
total_counts=1,
)
groups = [(0, ), (1, ), (2, 0)]
res_by_group = get_results_by_qubit_groups([er1, er2, er3, er4], groups)
assert res_by_group == {(0, ): [er1], (1, ): [er2], (0, 2): [er1, er4]}
def test_expt_settings_diagonal_in_tpb():
def _expt_settings_diagonal_in_tpb(es1: ExperimentSetting,
es2: ExperimentSetting):
"""
Extends the concept of being diagonal in the same tpb to ExperimentSettings, by
determining if the pairs of in_states and out_operators are separately diagonal in the same
tpb
"""
max_weight_in = _max_weight_state([es1.in_state, es2.in_state])
max_weight_out = _max_weight_operator(
[es1.out_operator, es2.out_operator])
return max_weight_in is not None and max_weight_out is not None
expt_setting1 = ExperimentSetting(plusZ(1) * plusX(0), sY(1) * sZ(0))
expt_setting2 = ExperimentSetting(plusY(2) * plusZ(1), sZ(2) * sY(1))
assert _expt_settings_diagonal_in_tpb(expt_setting1, expt_setting2)
expt_setting3 = ExperimentSetting(plusX(2) * plusZ(1), sZ(2) * sY(1))
expt_setting4 = ExperimentSetting(plusY(2) * plusZ(1), sX(2) * sY(1))
assert not _expt_settings_diagonal_in_tpb(expt_setting2, expt_setting3)
assert not _expt_settings_diagonal_in_tpb(expt_setting2, expt_setting4)
def test_max_tpb_overlap_1():
tomo_expt_settings = [
ExperimentSetting(plusZ(1) * plusX(0),
sY(2) * sY(1)),
ExperimentSetting(plusX(2) * plusZ(1),
sY(2) * sZ(0)),
]
tomo_expt_program = Program(H(0), H(1), H(2))
tomo_expt = Experiment(tomo_expt_settings, tomo_expt_program)
expected_dict = {
ExperimentSetting(
plusX(0) * plusZ(1) * plusX(2),
sZ(0) * sY(1) * sY(2)): [
ExperimentSetting(plusZ(1) * plusX(0),
sY(2) * sY(1)),
ExperimentSetting(plusX(2) * plusZ(1),
sY(2) * sZ(0)),
]
}
assert expected_dict == _max_tpb_overlap(tomo_expt)
def test_max_weight_state_4():
states = [plusX(1) * minusZ(0), plusX(0), minusZ(1)]
assert _max_weight_state(states) is None
def test_max_weight_state_3():
states = [plusX(0) * minusZ(1), plusX(0), minusZ(1)]
assert _max_weight_state(states) == states[0]
