Metadata-Version: 2.1
Name: krotov
Version: 0.2.0
Summary: Python implementation of Krotov's method for quantum optimal control
Home-page: https://github.com/qucontrol/krotov
Author: Michael Goerz
Author-email: mail@michaelgoerz.net
License: BSD license
Description: =====================
        Krotov Python Package
        =====================
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        Python implementation of Krotov's method for quantum optimal control.
        
        This implementation follows the original implementation in the `QDYN Fortran library`_.
        The method is described in detail in `D. M. Reich, M. Ndong, and C. P. Koch, J. Chem. Phys. 136, 104103 (2012) <https://doi.org/10.1063/1.3691827>`_ (`arXiv:1008.5126 <http://arxiv.org/abs/1008.5126>`_)
        
        The ``krotov`` package is built on top of `QuTiP`_.
        
        Development happens on `Github`_. You can read the full documentation at `ReadTheDocs`_.
        
        
        .. _QDYN Fortran library: https://www.qdyn-library.net
        .. _QuTiP: http://qutip.org
        .. _ReadTheDocs: https://krotov.readthedocs.io/en/latest/
        
        
        Purpose
        -------
        
        Optimal control is one of the cornerstones of quantum technology. It asks the
        question how to make a manipulate the dynamics of a quantum system behave some
        desired way. See `Glaser et al. Eur. Phys. J. D 69, 279 (2015)`_ for an
        overview of the research field.
        
        Krotov's method is one of the two leading gradient-based optimization
        algorithms used in quantum optimal control. To date, there has not been an open
        source implementation of the method. This package provides this missing
        implementation.
        
        The choice of Python as an implementation language is due to Python's easy to learn
        syntax, expressiveness, and immense popularity in the scientific community.
        Moreover, the `QuTiP`_ library exists to provide the foundations of
        numerically describing quantum systems, and already includes basic versions of
        some of the other popular algorithms in quantum control, the gradient-based
        GRAPE and the gradient-free CRAB. The availability of the `Jupyter notebook`_
        system provides an ideal platform for demonstrating the use of the method.
        
        
        The Krotov package is targeted both towards students wishing to enter
        the field of quantum control, and researchers in the field. By providing a rich
        set of examples of how the package can be used to reproduce the solutions of
        control problems from recent publications, we enable users of our package to
        explore how to formulate typical control problems, and how to use Krotov's
        method to solve them.
        
        The choice of Python implies that for large-scale control problems, performance may
        become a significant issue. In this case, it may be necessary to implement
        Krotov's method in a more efficient (compiled) language. While the method as
        such is relatively straightforward, there are some subtleties involved, which
        are explained both in the package documentation and in the source code. Thus,
        the Krotov package serves as a reference implementation, leveraging Python's
        reputation as "executable pseudocode", and as a foundation against which to test.
        
        .. _Glaser et al. Eur. Phys. J. D 69, 279 (2015): https://link.springer.com/article/10.1140%2Fepjd%2Fe2015-60464-1
        
        
        Prerequisites
        -------------
        
        The Krotov package is available for Python versions >= 3.5. Its main dependency is `QuTiP`_
        (apart from the `core packages of the Python scientific ecosystem`_).
        Thus, you should consider `QuTiP's installation instructions`_.
        
        In any case, using some sort of `virtual environment`_ is strongly encouraged.
        Most packages in the Python scientific ecosystem are now available as
        `wheels`_, making installation via `pip`_ easy. However, `QuTiP currently does
        not provide wheels`_. Thus, on systems that do not have the necessary compilers
        installed (Windows, macOS), the `conda`_ package manager provides a good solution.
        
        Assuming ``conda`` is installed (e.g. through `Miniconda`_), the following
        commands set up a virtual (conda) environment into which the Krotov package can
        then be installed:
        
        .. code-block:: console
        
            $ conda create -n qucontrolenv python=3.6
            $ conda activate qucontrolenv
            $ conda config --append channels conda-forge
            $ conda install qutip
        
        .. _core packages of the Python scientific ecosystem: https://www.scipy.org
        .. _QuTiP's installation instructions: http://qutip.org/docs/latest/installation.html
        .. _virtual environment: https://docs.python.org/3/glossary.html#term-virtual-environment
        .. _wheels: https://packaging.python.org/tutorials/installing-packages/#source-distributions-vs-wheels
        .. _QuTiP currently does not provide wheels: https://github.com/qutip/qutip/issues/933
        .. _conda: https://conda.io/docs/index.html
        .. _Miniconda: https://conda.io/miniconda.html
        
        
        Installation
        ------------
        To install the latest released version of ``krotov`` into your current (conda)
        environment, run this command in your terminal:
        
        .. code-block:: console
        
            $ pip install krotov
        
        This is the preferred method to install the ``krotov`` package, as it will always install the most recent stable release.
        
        You may also do
        
        .. code-block:: console
        
            $ pip install krotov[dev,extras]
        
        to install additional development dependencies, including packages required to run the example notebooks.
        
        If you don't have `pip`_ installed, this `Python installation guide`_, respectively the `Python Packaging User Guide`_ can guide
        you through the process.
        
        .. _pip: https://pip.pypa.io
        .. _Python installation guide: http://docs.python-guide.org/en/latest/starting/installation/
        .. _Python Packaging User Guide: https://packaging.python.org/tutorials/installing-packages/
        
        
        To install the latest development version of ``krotov`` from `Github`_:
        
        .. code-block:: console
        
            $ pip install git+https://github.com/qucontrol/krotov.git@master#egg=krotov
        
        .. _Github: https://github.com/qucontrol/krotov
        
        Usage
        -----
        
        To use Krotov's method for quantum optimal control in a Python script or
        `Jupyter notebook`_, start with::
        
            import krotov
        
        Then,
        
        * define the necessary quantum operators and states using `QuTiP`_.
        * create a list of objectives, as instances of
          |krotov.Objective|_
        * call |krotov.optimize_pulses|_ to perform an optimization of an arbitrary
          number of control fields over all the objectives.
        
        .. |krotov.Objective| replace:: ``krotov.Objective``
        .. _krotov.Objective: https://krotov.readthedocs.io/en/latest/API/krotov.objectives.html#krotov.objectives.Objective
        
        .. |krotov.optimize_pulses| replace:: ``krotov.optimize_pulses``
        .. _krotov.optimize_pulses: https://krotov.readthedocs.io/en/latest/API/krotov.optimize.html#krotov.optimize.optimize_pulses
        
        See `Using Krotov with QuTiP <https://krotov.readthedocs.io/en/latest/qutip_usage.html#using-krotov-with-qutip>`_ and `Examples <https://krotov.readthedocs.io/en/latest/examples.html#krotov-example-notebooks>`_ for details.
        
        .. _Jupyter notebook: http://jupyter.org
        
        
        =======
        History
        =======
        
        
        0.2.0 (2019-02-14)
        ------------------
        
        * Added: Implementation of all the standard functionals
        * Added: The ``info_hook`` receives additional information, including ∫gₐ(t)dt (#32)
        * Added: Initialization of objectives for gate optimization in Liouville space
        * Added: A new propagator ``DensityMatrixODEPropagator`` for faster density matrix propagation
        * Added: Support for "stateful" propagators by sublassing from ``krotov.propagators.Propagator``
        * Changed: more flexibility for parallelization (#29)
        * Added: Support for the second-order pulse update
        * Changed: The options for the controls (λₐ, update-shape) are now passed through a simplified ``dict`` interface, instead of a custom ``PulseOptions`` class.
        
        
        0.1.0 (2018-12-24)
        ------------------
        
        * Initial release with complete implementation of first-order Krotov's method
        * Support for state-to-state and gate optimization, for both closed and open systems
        
        
        0.0.1 (2018-11-06)
        ------------------
        
        * Non-functional placeholder release
        
Keywords: krotov
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Provides-Extra: extras
Provides-Extra: dev
