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)