Portfolio Optimization with VQE

Question

I'm working on a portfolio optimization problem using Qiskit and I'm encountering an error when trying to solve a quadratic program using MinimumEigenOptimizer with SamplingVQE. Any insights on what might be causing this error or how to fix it would be greatly appreciated!

Here's the code I'm using:

from qiskit_algorithms import SamplingVQE
from qiskit_finance.applications.optimization import PortfolioOptimization
from qiskit_finance.data_providers import RandomDataProvider
from qiskit_optimization.algorithms import MinimumEigenOptimizer
from qiskit_ibm_runtime import QiskitRuntimeService, Session, SamplerV2 as Sampler
from qiskit.circuit.library import RealAmplitudes
from qiskit.transpiler.preset_passmanagers import generate_preset_pass_manager
from qiskit_algorithms.optimizers import SLSQP
import numpy as np
import datetime

num_assets = 30
seed = 123

# Generate expected return and covariance matrix from (random) time-series
stocks = [("TICKER%s" % i) for i in range(num_assets)]
data = RandomDataProvider(
    tickers=stocks,
    start=datetime.datetime(2016, 1, 1),
    end=datetime.datetime(2016, 1, 30),
    seed=seed,
)
data.run()
mu = data.get_period_return_mean_vector()
sigma = data.get_period_return_covariance_matrix()

q = 0.5  # set risk factor
budget = num_assets // 2  # set budget
penalty = num_assets  # set parameter to scale the budget penalty term

portfolio = PortfolioOptimization(
    expected_returns=mu, covariances=sigma, risk_factor=q, budget=budget
)
qp = portfolio.to_quadratic_program()

service = QiskitRuntimeService(channel="ibm_quantum")
backend = service.least_busy(operational=True, simulator=False)
session = Session(service=service, backend=backend)

ansatz = RealAmplitudes(qp.get_num_binary_vars(), reps=3)
pm = generate_preset_pass_manager(backend=backend, optimization_level=2)
isa_circuit = pm.run(ansatz)

vqe = SamplingVQE(sampler=Sampler(session=session), ansatz= isa_circuit, optimizer=SLSQP())  
optimizer = MinimumEigenOptimizer(vqe)
result = optimizer.solve(qp)
print(result)

When I run this code, I get the following error:

TypeError: run() takes 2 positional arguments but 3 were given

Here's the full traceback:

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
...
File ~/opt/anaconda3/lib/python3.8/site-packages/qiskit_algorithms/minimum_eigensolvers/sampling_vqe.py:318, in SamplingVQE._get_evaluate_energy.<locals>.evaluate_energy(parameters)
    315 parameters = np.reshape(parameters, (-1, num_parameters)).tolist()
    316 batch_size = len(parameters)
--> 318 estimator_result = estimator.run(
    319     batch_size * [ansatz], batch_size * [operator], parameters
    320 ).result()
    321 values = estimator_result.values
    323 if self.callback is not None:

File ~/opt/anaconda3/lib/python3.8/site-packages/qiskit/primitives/primitive_job.py:51, in PrimitiveJob.result(self)
     49 def result(self) -> ResultT:
     50     self._check_submitted()
---> 51     return self._future.result()

File ~/opt/anaconda3/lib/python3.8/concurrent/futures/_base.py:437, in Future.result(self, timeout)
    435     raise CancelledError()
    436 elif self._state == FINISHED:
--> 437     return self.__get_result()
    439 self._condition.wait(timeout)
    441 if self._state in [CANCELLED, CANCELLED_AND_NOTIFIED]:

File ~/opt/anaconda3/lib/python3.8/concurrent/futures/_base.py:389, in Future.__get_result(self)
    387 if self._exception:
    388     try:
--> 389         raise self._exception
    390     finally:
    391         # Break a reference cycle with the exception in self._exception
    392         self = None

File ~/opt/anaconda3/lib/python3.8/concurrent/futures/thread.py:57, in _WorkItem.run(self)
     54     return
     56 try:
---> 57     result = self.fn(*self.args, **self.kwargs)
     58 except BaseException as exc:
     59     self.future.set_exception(exc)

File ~/opt/anaconda3/lib/python3.8/site-packages/qiskit_algorithms/minimum_eigensolvers/diagonal_estimator.py:117, in _DiagonalEstimator._call(self, circuits, observables, parameter_values, **run_options)
    110 def _call(
    111     self,
    112     circuits: Sequence[int],
   ...
    115     **run_options,
    116 ) -> _DiagonalEstimatorResult:
--> 117     job = self.sampler.run(
    118         [self._circuits[i] for i in circuits],
    119         parameter_values,
    120         **run_options,
    121     )
    122     sampler_result = job.result()
    123     samples = sampler_result.quasi_dists

TypeError: run() takes 2 positional arguments but 3 were given
```

Answer 1

Qiskit Optimization (ML, Finance and Nature) and Qiskit Algorithms all support only the V1 primitives. There are issues in all of the github repos of above for support of V2. So you need to use the V1 primitives for now.