https://github.com/quantumlib/qualtran
Qᴜᴀʟᴛʀᴀɴ is a Python library for expressing and analyzing Fault Tolerant Quantum algorithms.
https://github.com/quantumlib/qualtran
algorithms api cirq conversion google google-quantum python python3 quantum quantum-algorithms quantum-circuit quantum-computing quantum-information-science quantum-programming quantum-programming-language quantum-simulation research resource-estimation sdk
Last synced: 4 days ago
JSON representation
Qᴜᴀʟᴛʀᴀɴ is a Python library for expressing and analyzing Fault Tolerant Quantum algorithms.
- Host: GitHub
- URL: https://github.com/quantumlib/qualtran
- Owner: quantumlib
- License: apache-2.0
- Created: 2022-07-06T22:24:52.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2025-05-29T22:51:08.000Z (30 days ago)
- Last Synced: 2025-05-29T23:32:56.163Z (30 days ago)
- Topics: algorithms, api, cirq, conversion, google, google-quantum, python, python3, quantum, quantum-algorithms, quantum-circuit, quantum-computing, quantum-information-science, quantum-programming, quantum-programming-language, quantum-simulation, research, resource-estimation, sdk
- Language: Python
- Homepage: https://qualtran.readthedocs.io/en/latest/
- Size: 24.7 MB
- Stars: 214
- Watchers: 16
- Forks: 68
- Open Issues: 232
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
- Citation: CITATION.cff
- Security: .github/SECURITY.md
- Support: SUPPORT.md
Awesome Lists containing this project
README
Python package for fault-tolerant quantum algorithms research.
[](https://github.com/quantumlib/qualtran/blob/main/LICENSE)
[](https://www.python.org/downloads/)
[](https://pypi.org/project/qualtran)
[Installation](#installation) –
[Usage](#usage) –
[Documentation](#documentation) –
[Community](#community) –
[Citation](#citation) –
[Contact](#contact)
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](https://qualtran.readthedocs.io/en/latest/_infra/Bloqs-Tutorial.html) or investigate
the [bloqs library](https://qualtran.readthedocs.io/en/latest/bloqs/index.html#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].
[many open-source contributors]: https://github.com/quantumlib/Qualtran/graphs/contributors
[code of conduct]: https://github.com/quantumlib/Qualtran/blob/main/CODE_OF_CONDUCT.md
### 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.
[`qualtran-announce`]: https://groups.google.com/g/qualtran-announce
[repository notifications]: https://docs.github.com/github/managing-subscriptions-and-notifications-on-github/configuring-notifications
[Qualtran releases feed]: https://github.com/quantumlib/Qualtran/releases.atom
[PyPI releases feed]: https://pypi.org/rss/project/qualtran/releases.xml
### 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!
[`qualtran-dev`]: https://groups.google.com/g/qualtran-dev
### 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]!
[Open an issue on GitHub]: https://github.com/quantumlib/Qualtran/issues/new/choose
[contribution guidelines]: https://github.com/quantumlib/Qualtran/blob/main/CONTRIBUTING.md
[pull request]: https://help.github.com/articles/about-pull-requests
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},
}
```
## Contact
For any questions or concerns not addressed here, please email [email protected].
## Disclaimer
This is not an officially supported Google product.
This project is not eligible for the [Google Open Source Software Vulnerability Rewards
Program](https://bughunters.google.com/open-source-security).
Copyright 2025 Google LLC.
