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Python toolkit for quantum information theory

Project description

ToQITo (Theory of Quantum Information Toolkit)

The toqito package is a Python package for studying various aspects of quantum information theory. Specifically, toqito focuses on providing numerical tools to study problems pertaining to entanglement theory, nonlocal games, matrix analysis, and other aspects of quantum information that are often associated with computer science.

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toqito aims to fill the needs of quantum information researchers who want numerical and computational tools for manipulating quantum states, measurements, and channels. It can also be used as a tool to enhance the experience of students and instructors in classes pertaining to quantum information.

The inspiration for this package is heavily influenced by the QETLAB package in MATLAB by Nathaniel Johnston. Many of the functions found here are direct ports of those functions converted into Python code.


The preferred way to install the toqito package is via pip:

pip install toqito

Alternatively, to install, you may also run the following command from the top-level package directory.

python install


The documentation for toqito, along with specific examples of usage are provided on the documentation page.


The nose module is used for testing. To run the suite of tests for toqito, run the following command in the root directory of this project.

nosetests --with-coverage --cover-erase --cover-package toqito


You can cite toqito using the following DOI: 10.5281/zenodo.3699578

If you are using the toqito software package in research work, please include an explicit mention of toqito in your publication. Something along the lines of:

To solve problem "X" we used `toqito`; a package for studying certain
aspects of quantum information.

A BibTeX entry that you can use to cite toqito is provided here:

   author       = {Vincent Russo},
   title        = {toqito: A {P}ython toolkit for quantum information, version 0.0.2},
   howpublished = {\url{}},
   month        = Mar,
   year         = 2020,
   doi          = {10.5281/zenodo.3699578}


MIT License

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