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Quantum Information Toolkit

Project description


Quantum Information Toolkit (QIT) is a free, open source Python 3 package for various quantum information and computing -related purposes, released under GNU GPL v3. It is a descendant of the MATLAB Quantum Information Toolkit, and has considerably more functionality.

The latest version can be found on our website.

The toolkit is installed from the Python Package Index by

$ pip install qit

or by cloning the Git repository, and installing directly from there:

$ git clone qit
$ cd qit
$ pip install .

For interactive use, we recommend the IPython shell.

To get an overview of the features and capabilities of the toolkit, run

$ python qit/


QIT is released under the GNU General Public License version 3. This basically means that you can freely use, share and modify it as you wish, as long as you give proper credit to the authors and do not change the terms of the license. See LICENSE.txt for the details.

Design notes

The main design goals for this toolkit are ease of use and comprehensiveness. It is primarily meant to be used as a tool for experimentation, hypothesis testing, small simulations, and learning, not for computationally demanding simulations. Hence the efficiency of the algorithms used is not a number one priority. However, if you think an algorithm could be improved without compromising accuracy or maintainability, please let the authors know or become a contributor yourself!


QIT is an open source project and your contributions are welcome. To keep the code readable and maintainable, we ask you to follow these coding guidelines:

  • Fully document all the modules, classes and functions using docstrings (purpose, calling syntax, output, approximations used, assumptions made…). The docstrings may contain reStructuredText markup for math, citations etc. Use the Google docstring style.

  • Add relevant literature references to docs/refs.bib and cite them in the function or module docstring using sphinxcontrib-bibtex syntax.

  • Instead of using multiple similar functions, use a single function performing multiple related tasks, see e.g. qit.state.State.measure.

  • Raise an exception on invalid input.

  • Use variables sparingly, give them descriptive (but short) names.

  • Use brief comments to explain the logic of your code.

  • When you add new functions also add tests for validating your code. If you modify existing code, make sure you didn’t break anything by checking that the tests still run successfully.

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