Qiskit Algorithms

[!WARNING]
Qiskit Algorithms is no longer officially supported by IBM.
Like any other Apache 2 licensed code, you are free to use it or/and extend it, but please be aware that it is under your own risk.

Installation

We encourage installing Qiskit Algorithms via the pip tool (a python package manager).

pip install qiskit-algorithms

pip will handle all dependencies automatically and you will always install the latest (and well-tested) version.

If you want to work on the very latest work-in-progress versions, either to try features ahead of their official release or if you want to contribute to Algorithms, then you can install from source. To do this follow the instructions in the documentation.

Optional Installs

Some optimization algorithms require specific libraries to be run:

• Scikit-quant, may be installed using the command pip install scikit-quant.

• SnobFit, may be installed using the command pip install SQSnobFit.

• NLOpt, may be installed using the command pip install nlopt.

Contribution Guidelines

If you'd like to contribute to Qiskit Algorithms, please take a look at our contribution guidelines. This project adheres to Qiskit's code of conduct. By participating, you are expected to uphold this code.

We use GitHub issues for tracking requests and bugs. Please join the Qiskit Slack community and for discussion and simple questions. For questions that are more suited for a forum, we use the Qiskit tag in Stack Overflow.

Authors and Citation

Qiskit Algorithms was inspired, authored and brought about by the collective work of a team of researchers. Algorithms continues to grow with the help and work of many people, who contribute to the project at different levels. If you use Qiskit, please cite as per the provided BibTeX file.

License

This project uses the Apache License 2.0.