qiskit.algorithms.optimizers.ADAM.optimize

ADAM.optimize(num_vars, objective_function, gradient_function=None, variable_bounds=None, initial_point=None)

Perform optimization.

Parameters

• num_vars (int) – Number of parameters to be optimized.

• objective_function (Callable[[ndarray], float]) – Handle to a function that computes the objective function.

• gradient_function (Optional[Callable[[ndarray], float]]) – Handle to a function that computes the gradient of the objective function.

• variable_bounds (Optional[List[Tuple[float, float]]]) – deprecated

• initial_point (Optional[ndarray]) – The initial point for the optimization.

Return type

Tuple[ndarray, float, int]

Returns

A tuple (point, value, nfev) where

point: is a 1D numpy.ndarray[float] containing the solution

value: is a float with the objective function value

nfev: is the number of objective function calls