def test_hubbard_trotter_error_matches_low_depth_trotter_error(self):
hamiltonian = normal_ordered(fermi_hubbard(3, 3, 1., 2.3))
error_operator = (
fermionic_swap_trotter_error_operator_diagonal_two_body(
hamiltonian))
error_operator.compress()
# Unpack result into terms, indices they act on, and whether
# they're hopping operators.
result = simulation_ordered_grouped_low_depth_terms_with_info(
hamiltonian)
terms, indices, is_hopping = result
old_error_operator = low_depth_second_order_trotter_error_operator(
terms, indices, is_hopping, jellium_only=True)
old_error_operator -= error_operator
self.assertEqual(old_error_operator, FermionOperator.zero())
def test_1D_jellium_trotter_error_matches_low_depth_trotter_error(self):
hamiltonian = normal_ordered(jellium_model(
hypercube_grid_with_given_wigner_seitz_radius_and_filling(
1, 5, wigner_seitz_radius=10.,
spinless=True), spinless=True, plane_wave=False))
error_operator = (
fermionic_swap_trotter_error_operator_diagonal_two_body(
hamiltonian))
error_operator.compress()
# Unpack result into terms, indices they act on, and whether
# they're hopping operators.
result = simulation_ordered_grouped_low_depth_terms_with_info(
hamiltonian)
terms, indices, is_hopping = result
old_error_operator = low_depth_second_order_trotter_error_operator(
terms, indices, is_hopping, jellium_only=True)
old_error_operator -= error_operator
self.assertEqual(old_error_operator, FermionOperator.zero())
def fermionic_swap_trotter_error_operator_diagonal_two_body(hamiltonian):
"""Compute the fermionic swap network Trotter error of a diagonal
two-body Hamiltonian.
Args:
hamiltonian (FermionOperator): The diagonal Coulomb Hamiltonian to
compute the Trotter error for.
Returns:
error_operator: The second-order Trotter error operator.
Notes:
Follows Eq 9 of Poulin et al., arXiv:1406.4920, applied to the
Trotter step detailed in Kivlichan et al., arxiv:1711.04789.
"""
single_terms = numpy.array(
simulation_ordered_grouped_low_depth_terms_with_info(hamiltonian)[0])
# Cache the halved terms for use in the second commutator.
halved_single_terms = single_terms / 2.0
term_mode_mask = bit_mask_of_modes_acted_on_by_fermionic_terms(
single_terms, count_qubits(hamiltonian))
error_operator = FermionOperator.zero()
for beta, term_beta in enumerate(single_terms):
modes_acted_on_by_term_beta = set()
for beta_action in term_beta.terms:
modes_acted_on_by_term_beta.update(
set(operator[0] for operator in beta_action))
beta_mode_mask = numpy.logical_or.reduce(
[term_mode_mask[mode] for mode in modes_acted_on_by_term_beta])
# alpha_prime indices that could have a nonzero commutator, i.e.
# there's overlap between the modes the corresponding terms act on.
valid_alpha_primes = numpy.where(beta_mode_mask)[0]
# Only alpha_prime < beta enters the error operator; filter for this.
valid_alpha_primes = valid_alpha_primes[valid_alpha_primes < beta]
for alpha_prime in valid_alpha_primes:
term_alpha_prime = single_terms[alpha_prime]
inner_commutator_term = (
commutator_ordered_diagonal_coulomb_with_two_body_operator(
term_beta, term_alpha_prime))
modes_acted_on_by_inner_commutator = set()
for inner_commutator_action in inner_commutator_term.terms:
modes_acted_on_by_inner_commutator.update(
set(operator[0] for operator in inner_commutator_action))
# If the inner commutator has no action, the commutator is zero.
if not modes_acted_on_by_inner_commutator:
continue
inner_commutator_mask = numpy.logical_or.reduce([
term_mode_mask[mode]
for mode in modes_acted_on_by_inner_commutator
])
# alpha indices that could have a nonzero commutator.
valid_alphas = numpy.where(inner_commutator_mask)[0]
# Filter so alpha <= beta in the double commutator.
valid_alphas = valid_alphas[valid_alphas <= beta]
for alpha in valid_alphas:
# If alpha = beta, only use half the term.
if alpha != beta:
outer_term_alpha = single_terms[alpha]
else:
outer_term_alpha = halved_single_terms[alpha]
# Add the partial double commutator to the error operator.
commutator_ordered_diagonal_coulomb_with_two_body_operator(
outer_term_alpha,
inner_commutator_term,
prior_terms=error_operator)
# Divide by 12 to match the error operator definition.
error_operator /= 12.0
return error_operator