Getting the current variational parameters in Qiskit

Question

I am right now using variational quantum eigensolver (VQE) to calculate the ground state of some molecules, like H2, by qiskit. The quesiton is that how to get the current parameters of the varaional ansatz, like UCCSD for the following code.

import numpy as np
import pylab
import copy
from qiskit import BasicAer
from qiskit.aqua import QuantumInstance
from qiskit.aqua.algorithms import NumPyMinimumEigensolver, VQE
from qiskit.aqua.components.optimizers import SLSQP
from qiskit.chemistry.components.initial_states import HartreeFock
from qiskit.chemistry.components.variational_forms import UCCSD
from qiskit.chemistry.drivers import PySCFDriver, UnitsType, Molecule
from qiskit.chemistry.algorithms.ground_state_solvers import GroundStateEigensolver
from qiskit.chemistry.algorithms.ground_state_solvers.minimum_eigensolver_factories import VQEUCCSDFactory
from qiskit.chemistry.transformations import (FermionicTransformation,
                                              FermionicTransformationType,
                                              FermionicQubitMappingType)
from qiskit.chemistry.algorithms.ground_state_solvers.minimum_eigensolver_factories import VQEUCCSDFactory

molecule = Molecule(geometry=[['H', [0., 0., 0.]],
                              ['H', [0., 0., 0.735]]],
                     charge=0, multiplicity=1)
driver = PySCFDriver(molecule = molecule, unit=UnitsType.ANGSTROM, basis='sto3g')
transformation = FermionicTransformation(qubit_mapping=FermionicQubitMappingType.JORDAN_WIGNER)


vqe_solver = VQEUCCSDFactory(QuantumInstance(BasicAer.get_backend('statevector_simulator')))

calc = GroundStateEigensolver(transformation, vqe_solver)
res = calc.solve(driver)

print(res)

Also, I need to simulate the model in the presence of noise, so I need to extract the variational parameters to calculate other properties of the system.

Answer 1

What I would do here is get back the raw results of your res, and there are stocked the parameters of the Ansatz you are looking for :

my_res = res.raw_result
# The dict of each parameter and its associated value
my_param_dict = res.raw_result.optimal_parameters
# The array of all the values
my_param_list = res.raw_result.optimal_point
print(my_param_dict)
print(my_param_list)

And you get this :

{ParameterVectorElement(θ[0]): 2.0215741373141244e-08, ParameterVectorElement(θ[1]): 2.0215741373141244e-08, ParameterVectorElement(θ[2]): -0.11176259664828359}

[ 2.02157414e-08  2.02157414e-08 -1.11762597e-01]

There is also an option with VQE that is to use a callback function storing all the intermediate parameters, see the answer here that explains it very well.