Encontrar la energía del estado fundamental usando AdaptVQE

Esta guía describe cómo se puede utilizar el algoritmo AdaptVQE para encontrar soluciones del estado fundamental de problemas de ciencias naturales.

1. Obtenemos un ElectronicStructureProblem que queremos resolver:

from qiskit_nature.second_q.drivers import PySCFDriver
driver = PySCFDriver(atom="H 0 0 0; H 0 0 0.735", basis="sto-3g")
problem = driver.run()

2. Configuramos nuestro QubitMapper:

from qiskit_nature.second_q.mappers import JordanWignerMapper
mapper = JordanWignerMapper()

3. Configuramos nuestro ansatz:

from qiskit_nature.second_q.circuit.library import UCCSD, HartreeFock
ansatz = UCCSD(
    problem.num_spatial_orbitals,
    problem.num_particles,
    mapper,
    initial_state=HartreeFock(
        problem.num_spatial_orbitals,
        problem.num_particles,
        mapper,
    ),
)

4. Configuramos un VQE:

import numpy as np
from qiskit_algorithms import VQE
from qiskit_algorithms.optimizers import SLSQP
from qiskit.primitives import Estimator
vqe = VQE(Estimator(), ansatz, SLSQP())
vqe.initial_point = np.zeros(ansatz.num_parameters)

5. Configuramos el AdaptVQE:

from qiskit_algorithms import AdaptVQE
adapt_vqe = AdaptVQE(vqe)
adapt_vqe.supports_aux_operators = lambda: True  # temporary fix

6. Encapsulamos todo en un GroundStateEigensolver:

from qiskit_nature.second_q.algorithms import GroundStateEigensolver
solver = GroundStateEigensolver(mapper, adapt_vqe)

7. Resolvemos el problema:

result = solver.solve(problem)

print(f"Total ground state energy = {result.total_energies[0]:.4f}")

Total ground state energy = -1.1373