def test_experiment_result():
er = ExperimentResult(
setting=ExperimentSetting(plusX(0), sZ(0)),
expectation=0.9,
std_err=0.05,
total_counts=100,
)
assert str(er) == 'X0_0→(1+0j)*Z0: 0.9 +- 0.05'
def test_correct_experiment_result():
e = ExperimentResult(setting=ExperimentSetting(plusX(0), sZ(0)),
expectation=0.9,
std_err=0.05,
total_counts=100)
cal = ExperimentResult(setting=ExperimentSetting(plusX(0), sZ(0)),
expectation=0.95,
std_err=0.01,
total_counts=100)
corrected = ExperimentResult(
setting=ExperimentSetting(plusX(0), sZ(0)),
expectation=0.9473684210526316,
std_err=np.sqrt(ratio_variance(0.9, 0.05**2, 0.95, 0.01**2)),
raw_expectation=0.9,
raw_std_err=0.05,
calibration_expectation=0.95,
calibration_std_err=0.01,
calibration_counts=100,
total_counts=100,
)
assert corrected == correct_experiment_result(e, cal)
def test_lifted_state_operator_backwards_qubits():
xz_state = plusX(5) * minusZ(6)
plus = np.array([1, 1]) / np.sqrt(2)
plus = plus[:, np.newaxis]
proj_plus = plus @ plus.conj().T
assert proj_plus.shape == (2, 2)
one = np.array([0, 1])
one = one[:, np.newaxis]
proj_one = one @ one.conj().T
assert proj_one.shape == (2, 2)
np.testing.assert_allclose(np.kron(proj_plus, proj_one),
lifted_state_operator(xz_state, qubits=[6, 5]))
