def test_integration_jellium_hamiltonian_with_negation(self):
hamiltonian = normal_ordered(
jellium_model(Grid(2, 3, 1.), plane_wave=False))
part_a = FermionOperator.zero()
part_b = FermionOperator.zero()
add_to_a_or_b = 0 # add to a if 0; add to b if 1
for term, coeff in hamiltonian.terms.items():
# Partition terms in the Hamiltonian into part_a or part_b
if add_to_a_or_b:
part_a += FermionOperator(term, coeff)
else:
part_b += FermionOperator(term, coeff)
add_to_a_or_b ^= 1
reference = normal_ordered(commutator(part_a, part_b))
result = commutator_ordered_diagonal_coulomb_with_two_body_operator(
part_a, part_b)
self.assertTrue(result.isclose(reference))
negative = commutator_ordered_diagonal_coulomb_with_two_body_operator(
part_b, part_a)
result += negative
self.assertTrue(result.isclose(FermionOperator.zero()))
def benchmark_commutator_diagonal_coulomb_operators_2D_spinless_jellium(
side_length):
"""Test speed of computing commutators using specialized functions.
Args:
side_length: The side length of the 2D jellium grid. There are
side_length ** 2 qubits, and O(side_length ** 4) terms in the
Hamiltonian.
Returns:
runtime_commutator: The time it takes to compute a commutator, after
partitioning the terms and normal ordering, using the regular
commutator function.
runtime_diagonal_commutator: The time it takes to compute the same
commutator using methods restricted to diagonal Coulomb operators.
"""
hamiltonian = normal_ordered(
jellium_model(Grid(2, side_length, 1.), plane_wave=False))
part_a = FermionOperator.zero()
part_b = FermionOperator.zero()
add_to_a_or_b = 0 # add to a if 0; add to b if 1
for term, coeff in hamiltonian.terms.items():
# Partition terms in the Hamiltonian into part_a or part_b
if add_to_a_or_b:
part_a += FermionOperator(term, coeff)
else:
part_b += FermionOperator(term, coeff)
add_to_a_or_b ^= 1
start = time.time()
_ = normal_ordered(commutator(part_a, part_b))
end = time.time()
runtime_commutator = end - start
start = time.time()
_ = commutator_ordered_diagonal_coulomb_with_two_body_operator(
part_a, part_b)
end = time.time()
runtime_diagonal_commutator = end - start
return runtime_commutator, runtime_diagonal_commutator
import numpy
import cirq
import openfermion
from openfermioncirq.variational.ansatzes import SplitOperatorTrotterAnsatz
# Construct a Hubbard model Hamiltonian
hubbard_model = openfermion.fermi_hubbard(2, 2, 1., 4.)
hubbard_hamiltonian = openfermion.get_diagonal_coulomb_hamiltonian(
hubbard_model)
# Construct a jellium model Hamiltonian
grid = openfermion.Grid(2, 2, 1.0)
jellium = openfermion.jellium_model(grid, spinless=True, plane_wave=False)
jellium_hamiltonian = openfermion.get_diagonal_coulomb_hamiltonian(jellium)
# Construct a Hamiltonian of ones
ones_hamiltonian = openfermion.DiagonalCoulombHamiltonian(one_body=numpy.ones(
(5, 5)),
two_body=numpy.ones(
(5, 5)))
def test_split_operator_trotter_ansatz_params():
ansatz = SplitOperatorTrotterAnsatz(hubbard_hamiltonian)
assert (set(ansatz.params()) == {
cirq.Symbol(name)
for name in {
# Set parameters of jellium model.
wigner_seitz_radius = 5. # Radius per electron in Bohr radii.
n_dimensions = 2 # Number of spatial dimensions.
grid_length = 3 # Number of grid points in each dimension.
spinless = True # Whether to include spin degree of freedom or not.
n_electrons = 2 # Number of electrons.
# Figure out length scale based on Wigner-Seitz radius and construct a basis grid.
length_scale = openfermion.wigner_seitz_length_scale(wigner_seitz_radius,
n_electrons, n_dimensions)
grid = openfermion.Grid(n_dimensions, grid_length, length_scale)
# Initialize the model and compute its ground energy in the correct particle number manifold
fermion_hamiltonian = openfermion.jellium_model(grid,
spinless=spinless,
plane_wave=False)
hamiltonian_sparse = openfermion.get_sparse_operator(fermion_hamiltonian)
ground_energy, _ = openfermion.jw_get_ground_state_at_particle_number(
hamiltonian_sparse, n_electrons)
print('The ground energy of the jellium Hamiltonian at {} electrons is {}'.
format(n_electrons, ground_energy))
# Convert to DiagonalCoulombHamiltonian type.
hamiltonian = openfermion.get_diagonal_coulomb_hamiltonian(fermion_hamiltonian)
# Define the objective function
objective = openfermioncirq.HamiltonianObjective(hamiltonian)
# Create a swap network Trotter ansatz.
iterations = 1 # This is the number of Trotter steps to use in the ansatz.