:py:mod:`qsearch.solvers`
=========================

.. py:module:: qsearch.solvers

.. autoapi-nested-parse::

   Defines Solver, a class used to wrap various numerical optimizers for finding parameters such that an ansatz circuit is a solution to a target unitary.



Module Contents
---------------

Classes
~~~~~~~

.. autoapisummary::

   qsearch.solvers.Solver
   qsearch.solvers.CMA_Solver
   qsearch.solvers.COBYLA_Solver
   qsearch.solvers.DIY_Solver
   qsearch.solvers.BFGS_Jac_Solver
   qsearch.solvers.LeastSquares_Jac_Solver



Functions
~~~~~~~~~

.. autoapisummary::

   qsearch.solvers.default_solver



.. py:function:: default_solver(options, x0=None)

   Runs a complex list of tests to determine the best Solver for a specific situation.


.. py:class:: Solver


   This class is used to wrap numerical optimizers for circuit solving.

   .. py:property:: distance_metric


   .. py:method:: solve_for_unitary(circuit, options, x0=None)
      :abstractmethod:

      Finds the best parameters that minimize error_func or error_residuals between the unitary from the circuit and options.target.


   .. py:method:: __eq__(other)

      Return self==value.



.. py:class:: CMA_Solver


   Bases: :py:obj:`Solver`

   Uses cmaes gradient-free optimization from the cma package.

   .. py:method:: solve_for_unitary(circuit, options, x0=None)

      Finds the best parameters that minimize error_func or error_residuals between the unitary from the circuit and options.target.



.. py:class:: COBYLA_Solver


   Bases: :py:obj:`Solver`

   Uses cobyla gradient-free optimization from scipy.

   .. py:method:: solve_for_unitary(circuit, options, x0=None)

      Finds the best parameters that minimize error_func or error_residuals between the unitary from the circuit and options.target.



.. py:class:: DIY_Solver(f)


   Bases: :py:obj:`Solver`

   An easier way to wrap a numerical optimizer than writing your own Solver class.

   Uses the function f that takes in eval_func and initial_guess and returns the parameters that minimizes eval_func.

   .. py:method:: solve_for_unitary(circuit, options, x0=None)

      Finds the best parameters that minimize error_func or error_residuals between the unitary from the circuit and options.target.



.. py:class:: BFGS_Jac_Solver


   Bases: :py:obj:`Solver`

   A solver based on the BFGS implementation in scipy.  It requires gradients.

   .. py:method:: solve_for_unitary(circuit, options, x0=None)

      Finds the best parameters that minimize error_func or error_residuals between the unitary from the circuit and options.target.



.. py:class:: LeastSquares_Jac_Solver


   Bases: :py:obj:`Solver`

   Uses the Leavenberg-Marquardt least-squares optimizer in scipy.

   .. py:property:: distance_metric


   .. py:method:: solve_for_unitary(circuit, options, x0=None)

      Finds the best parameters that minimize error_func or error_residuals between the unitary from the circuit and options.target.