def expectation_values_from_rdms(
interactionrdm: str,
qubit_operator: str,
sort_terms: bool = False,
):
operator = load_qubit_operator(qubit_operator)
rdms = load_interaction_rdm(interactionrdm)
expecval = get_expectation_values_from_rdms(rdms, operator, sort_terms=sort_terms)
save_expectation_values(expecval, "expectation_values.json")
def test_get_expectation_values_from_rdms(interactionrdm, qubitoperator, sort_terms):
expecval = get_expectation_values_from_rdms(
interactionrdm, qubitoperator, sort_terms
)
assert len(expecval.values) == len(qubitoperator.terms)
if not sort_terms:
coeff = np.array(list(qubitoperator.terms.values()))
else:
terms_iterator = sorted(
qubitoperator.terms.items(), key=lambda x: abs(x[1]), reverse=True
)
coeff = np.array([coefficient for _, coefficient in terms_iterator])
energy_test = np.sum(coeff * expecval.values)
energy_ref = np.real(interactionrdm.expectation(qubitoperator))
assert math.isclose(energy_test, energy_ref)
[
(
group_comeasureable_terms_greedy(h2_hamiltonian, False),
ExpectationValues(np.ones(15)),
),
(
group_comeasureable_terms_greedy(h2_hamiltonian, False),
ExpectationValues(np.zeros(15)),
),
(
group_comeasureable_terms_greedy(h2_hamiltonian, False),
ExpectationValues(np.repeat(0.5, 15)),
),
(
group_comeasureable_terms_greedy(h2_hamiltonian, False),
get_expectation_values_from_rdms(rdms, h2_hamiltonian, False),
),
(
group_comeasureable_terms_greedy(h2_hamiltonian, True),
get_expectation_values_from_rdms(rdms, h2_hamiltonian, True),
),
(
group_comeasureable_terms_greedy(QubitOperator("2[]"), True),
get_expectation_values_from_rdms(rdms, QubitOperator("2[]"), True),
),
],
)
def test_compute_group_variances_without_ref(groups, expecval):
test_variances = compute_group_variances(groups, expecval)
test_ham_variance = np.sum(test_variances)
# Assemble H and compute its variances independently