GradientDescentState

qiskit.algorithms.optimizers.GradientDescentState(x, fun, jac, nfev, njev, nit, stepsize, learning_rate)

Bases: OptimizerState

State of GradientDescent.

Dataclass with all the information of an optimizer plus the learning_rate and the stepsize.

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Attributes

stepsize

float | None

Norm of the gradient on the last step.

learning_rate

LearningRate

Learning rate at the current step of the optimization process.

It behaves like a generator, (use next(learning_rate) to get the learning rate for the next step) but it can also return the current learning rate with learning_rate.current.

x

POINT

Current optimization parameters.

fun

Callable[[POINT], float] | None

Function being optimized.

jac

Callable[[POINT], POINT] | None

Jacobian of the function being optimized.

nfev

int | None

Number of function evaluations so far in the optimization.

njev

int | None

Number of jacobian evaluations so far in the opimization.

nit

int | None

Number of optimization steps performed so far in the optimization.