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PennyLaneAI / pennylane-qulacs

The PennyLane-Qulacs plugin integrates the Qulacs quantum computing framework with PennyLane's quantum machine learning capabilities.
https://docs.pennylane.ai/projects/qulacs
Apache License 2.0
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PennyLane-Qulacs Plugin #######################

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The PennyLane-Qulacs plugin integrates the Qulacs quantum computing framework with PennyLane's quantum machine learning capabilities.

PennyLane <https://docs.pennylane.ai>__ is a cross-platform Python library for quantum machine learning, automatic differentiation, and optimization of hybrid quantum-classical computations.

Qulacs <https://github.com/qulacs>__ is a software library for quantum computing, written in C++ and with GPU support.

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The plugin documentation can be found here: <https://docs.pennylane.ai/projects/qulacs>__.

Features

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Benchmarks

We ran a 100 executions of 4 layer quantum neural network strongly entangling layer <https://docs.pennylane.ai/en/latest/code/api/pennylane.StronglyEntanglingLayers.html>_ and compared the runtimes between CPU and GPU.

.. image:: https://raw.githubusercontent.com/soudy/pennylane-qulacs/master/images/qnn_cpu_vs_gpu.png :align: center :width: 60% :target: javascript:void(0);

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.. image:: https://raw.githubusercontent.com/soudy/pennylane-qulacs/master/images/qulacs_table.png :align: center :width: 60% :target: javascript:void(0);

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Installation

This plugin requires Python version 3.10 or above, as well as PennyLane and Qulacs. Installation of this plugin, as well as all dependencies, can be done using pip:

.. code-block:: bash

$ pip install pennylane-qulacs["cpu"]

Note that you need to include whether to install the CPU version (pennylane-qulacs["cpu"]) or the GPU version (pennylane-qulacs["gpu"]) of Qulacs for it to be installed correctly. Otherwise Qulacs will need to be installed independently:

.. code-block:: bash

pip install qulacs pennylane-qulacs

Alternatively, you can install PennyLane-Qulacs from the source code <https://github.com/PennyLaneAI/pennylane-qulacs>__ by navigating to the top directory and running:

.. code-block:: bash

$ python setup.py install

.. note::

Qulacs supports parallelized executions via OpenMP. To set the number of
threads to use during simulations you need to update the environment
variable ``OMP_NUM_THREADS``. It can be set using the UNIX command:

``export OMP_NUM_THREADS = 8``

where 8 can be replaced by the number of threads that you wish to use. By
default Qulacs uses all available threads. To restore the default behaviour,
simply remove the environment variable. It can be done using the UNIX command:

``unset OMP_NUM_THREADS``

See the `OpenMP documentation page for OMP_NUM_THREADS
<https://www.openmp.org/spec-html/5.0/openmpse50.html>`__ or `here
<https://en.wikipedia.org/wiki/Environment_variable>`__ for more details on
how to use environment variables.

Dependencies


PennyLane-Qulacs requires the following libraries be installed:

* `Python <http://python.org/>`__ >= 3.10

as well as the following Python packages:

* `PennyLane <http://docs.pennylane.ai/>`__ >= 0.9
* `Qulacs <https://docs.qulacs.org/en/latest/>`__  >= 0.1.9

If you currently do not have Python 3 installed, we recommend
`Anaconda for Python 3 <https://www.anaconda.com/download/>`__, a distributed version of Python packaged
for scientific computation.

Tests

To test that the PennyLane-Qulacs plugin is working correctly you can run

.. code-block:: bash

$ make test

in the source folder.

Documentation



To build the HTML documentation, go to the top-level directory and run:

.. code-block:: bash

  $ make docs

The documentation can then be found in the ``doc/_build/html/`` directory.

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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
=======

PennyLane-Qulacs is the work of `many contributors <https://github.com/PennyLaneAI/pennylane-qulacs/graphs/contributors>`__.

If you are doing research using PennyLane and PennyLane-Qulacs, please cite `our paper <https://arxiv.org/abs/1811.04968>`__:

    Ville Bergholm, Josh Izaac, Maria Schuld, Christian Gogolin, M. Sohaib Alam, Shahnawaz Ahmed,
    Juan Miguel Arrazola, Carsten Blank, Alain Delgado, Soran Jahangiri, Keri McKiernan, Johannes Jakob Meyer,
    Zeyue Niu, Antal Száva, and Nathan Killoran.
    *PennyLane: Automatic differentiation of hybrid quantum-classical computations.* 2018. arXiv:1811.04968

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Support
=======

- **Source Code:** https://github.com/PennyLaneAI/pennylane-qulacs
- **Issue Tracker:** https://github.com/PennyLaneAI/pennylane-qulacs/issues
- **PennyLane Forum:** https://discuss.pennylane.ai

If you are having issues, please let us know by posting the issue on our Github issue tracker, or
by asking a question in the forum.

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License
=======

The PennyLane-Qulacs 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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