def test_group_experiments_greedy():
ungrouped_tomo_expt = Experiment(
[
[
ExperimentSetting(
_pauli_to_product_state(
PauliTerm.from_compact_str("(1+0j)*Z7Y8Z1Y4Z2Y5Y0X6")),
PauliTerm.from_compact_str("(1+0j)*Z4X8Y5X3Y7Y1"),
)
],
[ExperimentSetting(plusZ(7), sY(1))],
],
program=Program(H(0), H(1), H(2)),
)
grouped_tomo_expt = group_settings(ungrouped_tomo_expt, method="greedy")
expected_grouped_tomo_expt = Experiment(
[[
ExperimentSetting(
TensorProductState.from_str(
"Z0_7 * Y0_8 * Z0_1 * Y0_4 * Z0_2 * Y0_5 * Y0_0 * X0_6"),
PauliTerm.from_compact_str("(1+0j)*Z4X8Y5X3Y7Y1"),
),
ExperimentSetting(plusZ(7), sY(1)),
]],
program=Program(H(0), H(1), H(2)),
)
assert grouped_tomo_expt == expected_grouped_tomo_expt
def test_merge_disjoint_experiments():
sett1 = ExperimentSetting(TensorProductState(), sX(0) * sY(1))
sett2 = ExperimentSetting(plusZ(1), sY(1))
sett3 = ExperimentSetting(plusZ(0), sX(0))
sett4 = ExperimentSetting(minusX(1), sY(1))
sett5 = ExperimentSetting(TensorProductState(), sZ(2))
expt1 = Experiment(settings=[sett1, sett2], program=Program(X(1)))
expt2 = Experiment(settings=[sett3, sett4], program=Program(Z(0)))
expt3 = Experiment(settings=[sett5], program=Program())
merged_expt = merge_disjoint_experiments([expt1, expt2, expt3])
assert len(merged_expt) == 2
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_tpb_overlap_3():
# add another ExperimentSetting to the above
expt_setting = ExperimentSetting(
_pauli_to_product_state(
PauliTerm.from_compact_str("(1+0j)*Z7Y8Z1Y4Z2Y5Y0X6")),
PauliTerm.from_compact_str("(1+0j)*Z4X8Y5X3Y7Y1"),
)
expt_setting2 = ExperimentSetting(plusZ(7), sY(1))
p = Program(H(0), H(1), H(2))
tomo_expt2 = Experiment([expt_setting, expt_setting2], p)
expected_dict2 = {expt_setting: [expt_setting, expt_setting2]}
assert expected_dict2 == _max_tpb_overlap(tomo_expt2)
def test_max_weight_state_2():
states = [plusX(1) * plusZ(0), plusX(0), plusZ(1)]
assert _max_weight_state(states) is None
def test_max_weight_state_1():
states = [plusX(0) * plusZ(1), plusX(0), plusZ(1)]
assert _max_weight_state(states) == states[0]