def test_qasm_aux_operators_normalized(self):
"""Test VQE with qasm_simulator returns normalized aux_operator eigenvalues."""
wavefunction = self.ry_wavefunction
vqe = VQE(ansatz=wavefunction, quantum_instance=self.qasm_simulator)
_ = vqe.compute_minimum_eigenvalue(operator=self.h2_op)
opt_params = [
3.50437328,
3.87415376,
0.93684363,
5.92219622,
-1.53527887,
1.87941418,
-4.5708326,
0.70187027,
]
vqe._ret.optimal_point = opt_params
vqe._ret.optimal_parameters = dict(
zip(sorted(wavefunction.parameters, key=lambda p: p.name),
opt_params))
with self.assertWarns(DeprecationWarning):
optimal_vector = vqe.get_optimal_vector()
self.assertAlmostEqual(sum(v**2 for v in optimal_vector.values()),
1.0,
places=4)
def test_qasm_aux_operators_normalized(self):
"""Test VQE with qasm_simulator returns normalized aux_operator eigenvalues."""
wavefunction = self.ry_wavefunction
vqe = VQE(self.h2_op,
wavefunction,
quantum_instance=self.qasm_simulator)
opt_params = [
3.50437328, 3.87415376, 0.93684363, 5.92219622, -1.53527887,
1.87941418, -4.5708326, 0.70187027
]
vqe._ret = {}
vqe._ret['opt_params'] = opt_params
vqe._ret['opt_params_dict'] = \
dict(zip(sorted(wavefunction.parameters, key=lambda p: p.name), opt_params))
optimal_vector = vqe.get_optimal_vector()
self.assertAlmostEqual(sum([v**2 for v in optimal_vector.values()]),
1.0,
places=4)
