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        "description": "Data Cybernetics qiskit-algorithms\n###################################\n\n.. image:: https://img.shields.io/travis/com/carstenblank/dc-qiskit-algorithms/master.svg?style=for-the-badge\n    :alt: Travis\n    :target: https://travis-ci.com/carstenblank/dc-qiskit-algorithms\n\n.. image:: https://img.shields.io/codecov/c/github/carstenblank/dc-qiskit-algorithms/master.svg?style=for-the-badge\n    :alt: Codecov coverage\n    :target: https://codecov.io/gh/carstenblank/dc-qiskit-algorithms\n\n.. image:: https://img.shields.io/codacy/grade/f4132f03ce224f82bd3e8ba436b52af3.svg?style=for-the-badge\n    :alt: Codacy grade\n    :target: https://www.codacy.com/app/carstenblank/dc-qiskit-algorithms?utm_source=github.com&amp;utm_medium=referral&amp;utm_content=carstenblank/dc-qiskit-algorithms&amp;utm_campaign=Badge_Grade\n\n.. image:: https://img.shields.io/readthedocs/dc-qiskit-algorithms.svg?style=for-the-badge\n    :alt: Read the Docs\n    :target: https://dc-qiskit-algorithms.readthedocs.io\n\n.. image:: https://img.shields.io/pypi/v/dc-qiskit-algorithms.svg?style=for-the-badge\n    :alt: PyPI\n    :target: https://pypi.org/project/dc-qiskit-algorithms\n\n.. image:: https://img.shields.io/pypi/pyversions/dc-qiskit-algorithms.svg?style=for-the-badge\n    :alt: PyPI - Python Version\n    :target: https://pypi.org/project/dc-qiskit-algorithms\n\n.. header-start-inclusion-marker-do-not-remove\n\n`qiskit <https://qiskit.org/documentation/>`_ is an open-source compilation framework capable of targeting various\ntypes of hardware and a high-performance quantum computer simulator with emulation capabilities, and various\ncompiler plug-ins.\n\nThis library sports some useful algorithms for quantum computers using qiskit as a basis.\n\n\nFeatures\n========\n\n* Multi Qubit Quantum Fourier Transform\n\n* Draper adder\n\n* Uniform Rotations\n\n* State Preparation\n\n.. header-end-inclusion-marker-do-not-remove\n.. installation-start-inclusion-marker-do-not-remove\n\nInstallation\n============\n\nThis library requires Python version 3.5 and above, as well as qiskit.\nInstallation of this plugin, as well as all dependencies, can be done using pip:\n\n.. code-block:: bash\n\n    $ python -m pip install dc_qiskit_algorithms\n\nTo test that the algorithms are working correctly you can run\n\n.. code-block:: bash\n\n    $ make test\n\n.. installation-end-inclusion-marker-do-not-remove\n.. gettingstarted-start-inclusion-marker-do-not-remove\n\nGetting started\n===============\n\nYou can use the state preparation as follows\n\n.. code-block:: python\n\n    from dc_qiskit_algorithms.M\u00f6tt\u00f6nenStatePrep import state_prep_m\u00f6tt\u00f6nen\n\n    vector = [-0.1, 0.2, -0.3, 0.4, -0.5, 0.6, -0.7, 0.8]\n    vector = numpy.asarray(vector)\n    vector = (1 / numpy.linalg.norm(vector)) * vector\n\n    qubits = int(numpy.log2(len(vector)))\n    reg = QuantumRegister(qubits, \"reg\")\n    c = ClassicalRegister(qubits, \"c\")\n    qc = QuantumCircuit(reg, c, name='state prep')\n    state_prep_m\u00f6tt\u00f6nen(qc, vector, reg)\n\nAfter this, the quantum circuit is prepared in the given state. All complex vectors are possible!\n\n.. gettingstarted-end-inclusion-marker-do-not-remove\n\nPlease refer to the `documentation of the dc qiskit algorithm Plugin <https://dc-qiskit-algorithms.readthedocs.io/>`_ .\n\n.. howtocite-start-inclusion-marker-do-not-remove\n\n\nContributing\n============\n\nWe welcome contributions - simply fork the repository of this plugin, and then make a\n`pull request <https://help.github.com/articles/about-pull-requests/>`_ containing your contribution.\nAll contributers to this plugin will be listed as authors on the releases.\n\nWe also encourage bug reports, suggestions for new features and enhancements, and even links to cool projects or applications built on PennyLane.\n\n\nAuthors\n=======\n\nCarsten Blank\n\n.. support-start-inclusion-marker-do-not-remove\n\nSupport\n=======\n\n- **Source Code:** https://github.com/carstenblank/qiskit-algorithms\n- **Issue Tracker:** https://github.com/carstenblank/qiskit_algorithms/issues\n\nIf you are having issues, please let us know by posting the issue on our Github issue tracker.\n\n.. support-end-inclusion-marker-do-not-remove\n.. license-start-inclusion-marker-do-not-remove\n\nLicense\n=======\n\nThe data cybernetics qiskit algorithms plugin is **free** and **open source**, released under\nthe `Apache License, Version 2.0 <https://www.apache.org/licenses/LICENSE-2.0>`_.\n\n.. license-end-inclusion-marker-do-not-remove\n\n\n",
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