quantumlib/Qualtran — Gitpedia

<div align="center"> <img alt="Qualtran logo" width="340px" src="https://raw.githubusercontent.com/quantumlib/Qualtran/refs/heads/main/docs/_static/qualtran-logo-mode-sensitive.svg"> <br>

Python package for fault-tolerant quantum algorithms research.

Installation –
Usage –
Documentation –
Community –
Citation –
Contact

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Qualtran is a set of abstractions for representing quantum programs and a library of quantum
algorithms expressed in that language to support quantum algorithms research.

Installation

Qualtran is being actively developed. We recommend installing from the source code.

The following commands will clone a copy of the repository, then install the Qualtran package in
your local Python environment as a local editable copy:

shell
git clone https://github.com/quantumlib/Qualtran.git
cd Qualtran/
pip install -e .

You can also install the latest tagged release using pip:

shell
pip install qualtran

You can also install the latest version of the main branch on GitHub:

shell
pip install git+https://github.com/quantumlib/Qualtran

Usage

[!WARNING]
Qualtran is an experimental preview release. We provide no backwards compatibility guarantees.
Some algorithms or library functionality may be incomplete or contain inaccuracies. Open issues or
contact the authors with bug reports or feedback.

You should be able to import the qualtran package into your interactive Python environment as
as well as your programs:

shell
import qualtran

If this is successful, you can move on to learning how to
write bloqs or investigate
the bloqs library.

Documentation

Documentation is available at https://qualtran.readthedocs.io/.

Community

Qualtran's community is growing rapidly, and if you'd like to join the many open-source
contributors to the Qualtran project, we welcome your participation! We are dedicated to
cultivating an open and inclusive community, and have a code of conduct.

Announcements

You can stay on top of Qualtran news using the approach that best suits your needs:

For releases and major announcements: join the low-volume mailing list qualtran-announce.
For releases only:
- Via GitHub notifications: configure repository notifications for Qualtran.
- Via RSS from GitHub: subscribe to the GitHub Qualtran releases feed.
- Via RSS from PyPI: subscribe to the PyPI releases feed for Qualtran.

Questions and Discussions

If you'd like to ask questions and participate in discussions, join the qualtran-dev
group/mailing list. By joining qualtran-dev, you will also get automated invites to the
biweekly Qualtran Sync meeting (below).
Would you like to get more involved in Qualtran development? The biweekly Qualtran Sync
is a virtual face-to-face meeting of contributors to discuss everything from issues to
ongoing efforts, as well as to ask questions. Become a member of qualtran-dev to get
an automatic meeting invitation!

Issues and Pull Requests

Do you have a feature request or want to report a bug? Open an issue on
GitHub to report it!
Do you have a code contribution? Read our contribution guidelines, then
open a pull request!

Citation<a name="how-to-cite"></a>

When publishing articles or otherwise writing about Qualtran, please cite the following:

bibtex
@misc{harrigan2024qualtran,
    title={Expressing and Analyzing Quantum Algorithms with Qualtran},
    author={Matthew P. Harrigan and Tanuj Khattar
        and Charles Yuan and Anurudh Peduri and Noureldin Yosri
        and Fionn D. Malone and Ryan Babbush and Nicholas C. Rubin},
    year={2024},
    eprint={2409.04643},
    archivePrefix={arXiv},
    primaryClass={quant-ph},
    doi={10.48550/arXiv.2409.04643},
    url={https://arxiv.org/abs/2409.04643},
}