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VQE

The Variational Quantum Eigensolver (VQE) is a hybrid quantum-classical algorithm designed to find the ground state energy of a Hamiltonian by variationally optimizing a parameterized quantum circuit. It's widely used in quantum chemistry to compute molecular ground state energies and electronic structure properties. Nevertheless, it can also be used to find the ground state of combinatorial optimization problems, like this implementation is intends to do.

Compatible Backends

Backend Default
IBMQuantum
IBMFakeBackend
AerSimulator

Initialization

Python
from luna_quantum.algorithms import VQE
from luna_quantum.solve.parameters.algorithms.base_params import ScipyOptimizerParams

algorithm = VQE(
    backend=None,
    ansatz='efficient_su2',
    ansatz_config={},
    shots=1024,
    optimizer=ScipyOptimizerParams(
        method='cobyla',
        tol=None,
        bounds=None,
        jac=None,
        hess=None,
        maxiter=100,
        options={}
    ),
    initial_params_seed=None,
    initial_params_range=(0, 6.283185307179586)
)

Usage

Python
from luna_quantum.algorithms import VQE

algorithm = VQE()
solve_job = algorithm.run(model, name="my-solve-job")