Metadata-Version: 1.2
Name: PennyLane-qiskit
Version: 0.0.8
Summary: PennyLane plugin for qiskit-terra
Home-page: http://data-cybernetics.com
Maintainer: Carsten Blank
Maintainer-email: blank@data-cybernetics.com
License: Apache License 2.0
Description: PennyLane qiskit Plugin
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        .. image:: https://img.shields.io/travis/com/XanaduAI/pennylane-qiskit/master.svg?style=for-the-badge
            :alt: Travis
            :target: https://travis-ci.com/XanaduAI/pennylane-qiskit
        
        .. image:: https://img.shields.io/codecov/c/github/XanaduAI/pennylane-qiskit/master.svg?style=for-the-badge
            :alt: Codecov coverage
            :target: https://codecov.io/gh/XanaduAI/pennylane-qiskit
        
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            :target: https://www.codacy.com/app/XanaduAI/pennylane-qiskit?utm_source=github.com&amp;utm_medium=referral&amp;utm_content=carstenblank/pennylane-qiskit&amp;utm_campaign=Badge_Grade
        
        .. image:: https://img.shields.io/readthedocs/pennylane-qiskit.svg?style=for-the-badge
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            :target: https://pennylane-qiskit.readthedocs.io
        
        .. image:: https://img.shields.io/pypi/v/PennyLane-qiskit.svg?style=for-the-badge
            :alt: PyPI
            :target: https://pypi.org/project/PennyLane-qiskit
        
        .. image:: https://img.shields.io/pypi/pyversions/PennyLane-qiskit.svg?style=for-the-badge
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            :target: https://pypi.org/project/PennyLane-qiskit
        
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        `PennyLane <https://pennylane.readthedocs.io>`_ is a cross-platform Python library for quantum machine
        learning, automatic differentiation, and optimization of hybrid quantum-classical computations.
        
        `qiskit <https://qiskit.org/documentation/>`_ is an open-source compilation framework capable of targeting various
        types of hardware and a high-performance quantum computer simulator with emulation capabilities, and various
        compiler plug-ins.
        
        This PennyLane plugin allows to use both the software and hardware backends of qiskit as devices for PennyLane.
        
        
        Features
        ========
        
        * Provides three devices to be used with PennyLane: ``qiskit.basicaer``, ``qiskit.aer`` and ``qiskit.ibmq``. These devices provide access to the various backends.
        
        * Supports a wide range of PennyLane operations and expectation values across the providers.
        
        * Combine qiskit high performance simulator and hardware backend support with PennyLane's automatic differentiation and optimization.
        
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        Installation
        ============
        
        This plugin requires Python version 3.5 and above, as well as PennyLane and qiskit.
        Installation of this plugin, as well as all dependencies, can be done using pip:
        
        .. code-block:: bash
        
            $ python -m pip install pennylane_qiskit
        
        To test that the PennyLane qiskit plugin is working correctly you can run
        
        .. code-block:: bash
        
            $ make test
        
        in the source folder. Tests restricted to a specific provider can be run by executing :code:`make test-basicaer`,
        :code:`make test-aer` or :code:`make test-ibmq`.
        
        .. note::
            Tests on the `IBMQ device <https://pennylane-qiskit.readthedocs.io/en/latest/devices.html>`_ can
            only be run if a :code:`ibmqx_token` for the `IBM Q experience <https://quantumexperience.ng.bluemix.net/qx/experience>`_ is
            configured in the `PennyLane configuration file <https://pennylane.readthedocs.io/configuration.html>`_.
            If this is the case, running :code:`make test` also executes tests on the :code:`ibmq` device. By default tests on
            the :code:`ibmq` device run with :code:`ibmq_qasm_simulator` backend and those done by the :code:`basicaer` and
            :code:`aer` device are run with the :code:`qasm_simulator` backend. At the time of writing this means that the test are "free".
            Please verify that this is also the case for your account.
        
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        Getting started
        ===============
        
        You can instantiate a :code:`'qiskit.aer'` device for PennyLane with:
        
        .. code-block:: python
        
            import pennylane as qml
            dev = qml.device('qiskit.aer', wires=2)
        
        This device can then be used just like other devices for the definition and evaluation of QNodes within PennyLane.
        A simple quantum function that returns the expectation value of a measurement and depends on three classical input
        parameters would look like:
        
        .. code-block:: python
        
            @qml.qnode(dev)
            def circuit(x, y, z):
                qml.RZ(z, wires=[0])
                qml.RY(y, wires=[0])
                qml.RX(x, wires=[0])
                qml.CNOT(wires=[0, 1])
                return qml.expval.PauliZ(wires=1)
        
        You can then execute the circuit like any other function to get the quantum mechanical expectation value.
        
        .. code-block:: python
        
            circuit(0.2, 0.1, 0.3)
        
        You can also change the default device's backend with
        
        .. code-block:: python
        
            dev = qml.device('qiskit.aer', wires=2, backend='unitary_simulator')
        
        To get a current overview what backends are available you can query this by
        
        .. code-block:: python
        
            dev.capabilities()['backend']
        
        While the device :code:`'qiskit.aer'` is the standard go-to simulator that is provided along the `qiskit` main package
        installation, there exists a natively included python simulator that is slower but will work usually without the need
        to check out other dependencies (gcc, blas and so on) which can be sed by :code:`'qiskit.basicaer'`.
        There is an important difference of the two: while :code:`'qiskit.aer'` supports a simulation with noise
        :code:`'qiskit.basicaer'` does not.
        
        You can instantiate a noise model and apply it to the device by calling
        
        .. code-block:: python
        
            import pennylane as qml
        
            import qiskit
            from qiskit.providers.aer.noise.device import basic_device_noise_model
        
            qiskit.IBMQ.load_accounts()
            ibmqx4 = qiskit.IBMQ.get_backend('ibmqx4')
            device_properties = ibmqx4.properties()
        
            noise_model = basic_device_noise_model(device_properties)
        
            dev = qml.device('qiskit.aer', wires=2, noise_model=noise_model)
        
        Then all simulations are done with noise. The basic noise model is explained a little at
        `qiskit's documentation <https://qiskit.org/documentation/aer/device_noise_simulation.html>`_.
        
        Finally one of the more interesting functionality is running your code through the IBM Quantum Experience API.
        You can choose between different `backends` having either simulators or real hardware depending on your agreement with
        IBM.
        To use this device you would instantiate a :code:`'qiskit.ibmq'` device by giving your IBM Quantum Experience token:
        
        .. code-block:: python
        
            import pennylane as qml
            dev = qml.device('qiskit.ibmq', wires=2, ibmqx_token="XXX")
        
        In order to avoid accidentally publishing your token, you should better specify it via the
        `PennyLane configuration file <https://pennylane.readthedocs.io/en/latest/code/configuration.html>`__ by
        adding a section such as
        
        .. code::
        
          [qiskit.global]
        
            [qiskit.ibmq]
            ibmqx_token = "XXX"
        
        It is also possible to define an environment variable :code:`IBMQX_TOKEN`, from which the token will be taken if not provided in another way.
        
        Per default the backend :code:`ibmq` uses the simulator backend :code:`ibmq_qasm_simulator`, but you can change that
        to be any of the real backends as given by
        
        .. code-block:: python
        
            dev.capabilities()['backend']
        
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        Please refer to the `documentation of the PennyLane qiskit Plugin <https://pennylane-qiskit.readthedocs.io/>`_ as
        well as well as to the `documentation of PennyLane <https://pennylane.readthedocs.io/>`_ for further reference.
        
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        How to cite
        ===========
        
        If you are doing research using PennyLane, please cite `our whitepaper <https://arxiv.org/abs/1811.04968>`_:
        
          Ville Bergholm, Josh Izaac, Maria Schuld, Christian Gogolin, Carsten Blank, Keri McKiernan and Nathan Killoran. PennyLane. *arXiv*, 2018. arXiv:1811.04968
        
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        Contributing
        ============
        
        We welcome contributions - simply fork the repository of this plugin, and then make a
        `pull request <https://help.github.com/articles/about-pull-requests/>`_ containing your contribution.
        All contributers to this plugin will be listed as authors on the releases.
        
        We also encourage bug reports, suggestions for new features and enhancements, and even links to cool projects or applications built on PennyLane.
        
        
        Authors
        =======
        
        Carsten Blank, Sebastian Boerakker, Christian Gogolin, Josh Izaac
        
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        Support
        =======
        
        - **Source Code:** https://github.com/carstenblank/pennylane-qiskit
        - **Issue Tracker:** https://github.com/carstenblank/pennylane-qiskit/issues
        
        If you are having issues, please let us know by posting the issue on our Github issue tracker.
        
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        License
        =======
        
        The PennyLane qiskit plugin is **free** and **open source**, released under
        the `Apache License, Version 2.0 <https://www.apache.org/licenses/LICENSE-2.0>`_.
        
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Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Environment :: Console
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Natural Language :: English
Classifier: Operating System :: POSIX
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: POSIX :: Linux
Classifier: Operating System :: Microsoft :: Windows
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Topic :: Scientific/Engineering :: Physics
Provides: pennylane_qiskit
