qilisdk.utils.classical_solvers.scipy_solver

Classes

ScipySolver

Classical solver that uses SciPy to minimize the model's objective.

Module Contents

class ScipySolver(method: str | Callable | None = None, **kwargs: dict[str, Any])

Bases: qilisdk.utils.classical_solvers.base_solver.ClassicalSolver

Classical solver that uses SciPy to minimize the model’s objective.

This uses the existing QiliSDK SciPyOptimizer (the one used for variational algorithms) to optimize the model function.

Ejemplo

from qilisdk.core import Model
from qilisdk.utils.classical_solvers import ScipySolver

model = Model.knapsack(values=[5, 4], weights=[3, 2], max_weight=3)
result = ScipySolver(method="l-bfgs-b").solve(model)

Create a new SciPy based classical solver instance.

Parámetros:

method (str | Callable | None, optional) – The SciPy optimizer to use. See SciPyOptimizer for the full list of supported methods. If not given, SciPy chooses a default local minimizer.

Extra Args:

Any argument supported by scipy.optimize.minimize (or the corresponding global optimizer) can be passed and is forwarded to the underlying SciPyOptimizer.

method = None

extra_arguments

solve(model: qilisdk.core.Model) → qilisdk.utils.classical_solvers.base_solver.ClassicalSolverResult

Solve the given model by minimizing its objective with SciPy.

Parámetros:

model – The Model instance to solve.

Devuelve:

the results of the optimization, including the objective value and best solution.

Tipo del valor devuelto:

ClassicalSolverResult

Muestra:

ValueError – if the model contains a variable that is not a BinaryVariable, a SpinVariable or a Variable.