qubit_op = converter.convert(main_op, num_particles=num_particles)
# setup the initial state for the ansatz
from qiskit_nature.circuit.library import HartreeFock
init_state = HartreeFock(num_spin_orbitals, num_particles, converter)
# setup the ansatz for VQE
from qiskit.circuit.library import TwoLocal
ansatz = TwoLocal(num_spin_orbitals, ['ry', 'rz'], 'cz')
# add the initial state
ansatz.compose(init_state, front=True)
# set the backend for the quantum computation
from qiskit import Aer
backend = Aer.get_backend('aer_simulator_statevector')
# setup and run VQE
from qiskit.algorithms import VQE
algorithm = VQE(ansatz, optimizer=optimizer, quantum_instance=backend)
result = algorithm.compute_minimum_eigenvalue(qubit_op)
print(result.eigenvalue.real)
electronic_structure_result = problem.interpret(result)
print(electronic_structure_result)
def test_readme_sample(self):
""" readme sample test """
# pylint: disable=import-outside-toplevel,redefined-builtin
def print(*args):
""" overloads print to log values """
if args:
self.log.debug(args[0], *args[1:])
# --- Exact copy of sample code ----------------------------------------
from qiskit_nature.drivers import PySCFDriver, UnitsType
from qiskit_nature.problems.second_quantization.electronic import ElectronicStructureProblem
# Use PySCF, a classical computational chemistry software
# package, to compute the one-body and two-body integrals in
# electronic-orbital basis, necessary to form the Fermionic operator
driver = PySCFDriver(atom='H .0 .0 .0; H .0 .0 0.735',
unit=UnitsType.ANGSTROM,
basis='sto3g')
problem = ElectronicStructureProblem(driver)
# generate the second-quantized operators
second_q_ops = problem.second_q_ops()
main_op = second_q_ops[0]
num_particles = (problem.molecule_data_transformed.num_alpha,
problem.molecule_data_transformed.num_beta)
num_spin_orbitals = 2 * problem.molecule_data.num_molecular_orbitals
# setup the classical optimizer for VQE
from qiskit.algorithms.optimizers import L_BFGS_B
optimizer = L_BFGS_B()
# setup the mapper and qubit converter
from qiskit_nature.mappers.second_quantization import ParityMapper
from qiskit_nature.converters.second_quantization import QubitConverter
mapper = ParityMapper()
converter = QubitConverter(mapper=mapper, two_qubit_reduction=True)
# map to qubit operators
qubit_op = converter.convert(main_op, num_particles=num_particles)
# setup the initial state for the ansatz
from qiskit_nature.circuit.library import HartreeFock
init_state = HartreeFock(num_spin_orbitals, num_particles, converter)
# setup the ansatz for VQE
from qiskit.circuit.library import TwoLocal
ansatz = TwoLocal(num_spin_orbitals, ['ry', 'rz'], 'cz')
# add the initial state
ansatz.compose(init_state, front=True)
# set the backend for the quantum computation
from qiskit import Aer
backend = Aer.get_backend('statevector_simulator')
# setup and run VQE
from qiskit.algorithms import VQE
algorithm = VQE(ansatz, optimizer=optimizer, quantum_instance=backend)
result = algorithm.compute_minimum_eigenvalue(qubit_op)
print(result.eigenvalue.real)
electronic_structure_result = problem.interpret(result)
print(electronic_structure_result)
# ----------------------------------------------------------------------
self.assertAlmostEqual(result.eigenvalue.real,
-1.8572750301938803,
places=6)