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---
title: POWELL
description: API reference for qiskit.algorithms.optimizers.POWELL
in_page_toc_min_heading_level: 1
python_api_type: class
python_api_name: qiskit.algorithms.optimizers.POWELL
---
# POWELL
<Class id="qiskit.algorithms.optimizers.POWELL" isDedicatedPage={true} github="https://github.com/qiskit/qiskit/tree/stable/0.23/qiskit/algorithms/optimizers/powell.py" signature="POWELL(maxiter=None, maxfev=1000, disp=False, xtol=0.0001, tol=None, options=None, **kwargs)" modifiers="class">
Bases: [`qiskit.algorithms.optimizers.scipy_optimizer.SciPyOptimizer`](qiskit.algorithms.optimizers.SciPyOptimizer "qiskit.algorithms.optimizers.scipy_optimizer.SciPyOptimizer")
Powell optimizer.
The Powell algorithm performs unconstrained optimization; it ignores bounds or constraints. Powell is a *conjugate direction method*: it performs sequential one-dimensional minimization along each directional vector, which is updated at each iteration of the main minimization loop. The function being minimized need not be differentiable, and no derivatives are taken.
Uses scipy.optimize.minimize Powell. For further detail, please refer to See [https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.minimize.html](https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.minimize.html)
**Parameters**
* **maxiter** (`Optional`\[`int`]) Maximum allowed number of iterations. If both maxiter and maxfev are set, minimization will stop at the first reached.
* **maxfev** (`int`) Maximum allowed number of function evaluations. If both maxiter and maxfev are set, minimization will stop at the first reached.
* **disp** (`bool`) Set to True to print convergence messages.
* **xtol** (`float`) Relative error in solution xopt acceptable for convergence.
* **tol** (`Optional`\[`float`]) Tolerance for termination.
* **options** (`Optional`\[`dict`]) A dictionary of solver options.
* **kwargs** additional kwargs for scipy.optimize.minimize.
## Methods
### get\_support\_level
<Function id="qiskit.algorithms.optimizers.POWELL.get_support_level" signature="POWELL.get_support_level()">
Return support level dictionary
</Function>
### gradient\_num\_diff
<Function id="qiskit.algorithms.optimizers.POWELL.gradient_num_diff" signature="POWELL.gradient_num_diff(x_center, f, epsilon, max_evals_grouped=None)" modifiers="static">
We compute the gradient with the numeric differentiation in the parallel way, around the point x\_center.
**Parameters**
* **x\_center** (*ndarray*) point around which we compute the gradient
* **f** (*func*) the function of which the gradient is to be computed.
* **epsilon** (*float*) the epsilon used in the numeric differentiation.
* **max\_evals\_grouped** (*int*) max evals grouped, defaults to 1 (i.e. no batching).
**Returns**
the gradient computed
**Return type**
grad
</Function>
### minimize
<Function id="qiskit.algorithms.optimizers.POWELL.minimize" signature="POWELL.minimize(fun, x0, jac=None, bounds=None)">
Minimize the scalar function.
**Parameters**
* **fun** (`Callable`\[\[`Union`\[`float`, `ndarray`]], `float`]) The scalar function to minimize.
* **x0** (`Union`\[`float`, `ndarray`]) The initial point for the minimization.
* **jac** (`Optional`\[`Callable`\[\[`Union`\[`float`, `ndarray`]], `Union`\[`float`, `ndarray`]]]) The gradient of the scalar function `fun`.
* **bounds** (`Optional`\[`List`\[`Tuple`\[`float`, `float`]]]) Bounds for the variables of `fun`. This argument might be ignored if the optimizer does not support bounds.
**Return type**
[`OptimizerResult`](qiskit.algorithms.optimizers.OptimizerResult "qiskit.algorithms.optimizers.optimizer.OptimizerResult")
**Returns**
The result of the optimization, containing e.g. the result as attribute `x`.
</Function>
### print\_options
<Function id="qiskit.algorithms.optimizers.POWELL.print_options" signature="POWELL.print_options()">
Print algorithm-specific options.
</Function>
### set\_max\_evals\_grouped
<Function id="qiskit.algorithms.optimizers.POWELL.set_max_evals_grouped" signature="POWELL.set_max_evals_grouped(limit)">
Set max evals grouped
</Function>
### set\_options
<Function id="qiskit.algorithms.optimizers.POWELL.set_options" signature="POWELL.set_options(**kwargs)">
Sets or updates values in the options dictionary.
The options dictionary may be used internally by a given optimizer to pass additional optional values for the underlying optimizer/optimization function used. The options dictionary may be initially populated with a set of key/values when the given optimizer is constructed.
**Parameters**
**kwargs** (*dict*) options, given as name=value.
</Function>
### wrap\_function
<Function id="qiskit.algorithms.optimizers.POWELL.wrap_function" signature="POWELL.wrap_function(function, args)" modifiers="static">
Wrap the function to implicitly inject the args at the call of the function.
**Parameters**
* **function** (*func*) the target function
* **args** (*tuple*) the args to be injected
**Returns**
wrapper
**Return type**
function\_wrapper
</Function>
## Attributes
### bounds\_support\_level
<Attribute id="qiskit.algorithms.optimizers.POWELL.bounds_support_level">
Returns bounds support level
</Attribute>
### gradient\_support\_level
<Attribute id="qiskit.algorithms.optimizers.POWELL.gradient_support_level">
Returns gradient support level
</Attribute>
### initial\_point\_support\_level
<Attribute id="qiskit.algorithms.optimizers.POWELL.initial_point_support_level">
Returns initial point support level
</Attribute>
### is\_bounds\_ignored
<Attribute id="qiskit.algorithms.optimizers.POWELL.is_bounds_ignored">
Returns is bounds ignored
</Attribute>
### is\_bounds\_required
<Attribute id="qiskit.algorithms.optimizers.POWELL.is_bounds_required">
Returns is bounds required
</Attribute>
### is\_bounds\_supported
<Attribute id="qiskit.algorithms.optimizers.POWELL.is_bounds_supported">
Returns is bounds supported
</Attribute>
### is\_gradient\_ignored
<Attribute id="qiskit.algorithms.optimizers.POWELL.is_gradient_ignored">
Returns is gradient ignored
</Attribute>
### is\_gradient\_required
<Attribute id="qiskit.algorithms.optimizers.POWELL.is_gradient_required">
Returns is gradient required
</Attribute>
### is\_gradient\_supported
<Attribute id="qiskit.algorithms.optimizers.POWELL.is_gradient_supported">
Returns is gradient supported
</Attribute>
### is\_initial\_point\_ignored
<Attribute id="qiskit.algorithms.optimizers.POWELL.is_initial_point_ignored">
Returns is initial point ignored
</Attribute>
### is\_initial\_point\_required
<Attribute id="qiskit.algorithms.optimizers.POWELL.is_initial_point_required">
Returns is initial point required
</Attribute>
### is\_initial\_point\_supported
<Attribute id="qiskit.algorithms.optimizers.POWELL.is_initial_point_supported">
Returns is initial point supported
</Attribute>
### setting
<Attribute id="qiskit.algorithms.optimizers.POWELL.setting">
Return setting
</Attribute>
### settings
<Attribute id="qiskit.algorithms.optimizers.POWELL.settings">
**Return type**
`Dict`\[`str`, `Any`]
</Attribute>
</Class>