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qutip-qip

The qutip-qip package used to be a module qutip.qip under QuTiP (Quantum Toolbox in Python). From QuTiP 5.0, the community has decided to decrease the size of the core QuTiP package by reducing the external dependencies, in order to simplify maintenance. Hence a few modules are separated from the core QuTiP and will become QuTiP family packages. They are still maintained by the QuTiP team but hosted under different repositories in the QuTiP organization.

The qutip-qip package, QuTiP quantum information processing, aims at providing basic tools for quantum computing simulation both for simple quantum algorithm design and for experimental realization. Compared to other libraries for quantum information processing, qutip-qip puts additional emphasis on the physics layer and the interaction with the QuTiP package. The package offers two different approaches for simulating quantum circuits, one with QubitCircuit calculating unitary evolution under quantum gates by matrix product, another called Processor using open system solvers in QuTiP to simulate noisy quantum device.

Installation

To install the package, download to source code and run

    pip install .

under the directory containing the setup.py file.

If you want to edit the source code, use instead

    pip install -e .

To build and test the documentation, the following packages are required:

    sphinx numpydoc sphinx_rtd_theme doctest

Under the docs directory, use

    make html

to build the documentation.

Support

This package is supported and maintained by the same developers group as QuTiP.

Powered by NumFOCUS Unitary Fund

QuTiP development is supported by Nori's lab at RIKEN, by the University of Sherbrooke, by Chalmers University of Technology, by Macquarie University and by Aberystwyth University, among other supporting organizations.

License

license

You are free to use this software, with or without modification, provided that the conditions listed in the LICENSE.txt file are satisfied.

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The QuTiP quantum information processing package

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  • Python 99.7%
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