def test_vqe_adapt(self):
""" VQEAdapt test """
try:
# pylint: disable=import-outside-toplevel
from qiskit import Aer
except Exception as ex: # pylint: disable=broad-except
self.skipTest(
"Aer doesn't appear to be installed. Error: '{}'".format(
str(ex)))
return
self.var_form_base = UCCSD(self.num_qubits,
1,
self.num_spin_orbitals,
self.num_particles,
initial_state=self.init_state)
backend = Aer.get_backend('statevector_simulator')
optimizer = L_BFGS_B()
algorithm = VQEAdapt(self.qubit_op,
self.var_form_base,
optimizer,
threshold=0.00001,
delta=0.1)
result = algorithm.run(backend)
self.assertAlmostEqual(result.eigenvalue.real, -1.85727503, places=2)
self.assertIsNotNone(result.num_iterations)
self.assertIsNotNone(result.final_max_gradient)
self.assertIsNotNone(result.finishing_criterion)
def test_vqe_adapt(self):
""" VQEAdapt test """
try:
# pylint: disable=import-outside-toplevel
from qiskit import Aer
backend = Aer.get_backend('statevector_simulator')
except ImportError as ex: # pylint: disable=broad-except
self.skipTest(
"Aer doesn't appear to be installed. Error: '{}'".format(
str(ex)))
return
self.var_form_base = UCCSD(self.num_spin_orbitals,
self.num_particles,
initial_state=self.init_state)
optimizer = L_BFGS_B()
warnings.filterwarnings('ignore', category=DeprecationWarning)
algorithm = VQEAdapt(self.qubit_op,
self.var_form_base,
optimizer,
threshold=0.00001,
delta=0.1,
max_iterations=1)
warnings.filterwarnings('always', category=DeprecationWarning)
result = algorithm.run(backend)
self.assertEqual(result.num_iterations, 1)
self.assertEqual(result.finishing_criterion,
'Maximum number of iterations reached')
warnings.filterwarnings('ignore', category=DeprecationWarning)
algorithm = VQEAdapt(self.qubit_op,
self.var_form_base,
optimizer,
threshold=0.00001,
delta=0.1)
warnings.filterwarnings('always', category=DeprecationWarning)
result = algorithm.run(backend)
self.assertAlmostEqual(result.eigenvalue.real, -1.85727503, places=2)
self.assertEqual(result.num_iterations, 2)
self.assertAlmostEqual(result.final_max_gradient, 0.0, places=5)
self.assertEqual(result.finishing_criterion, 'Threshold converged')