Welcome to the Qiskit Tutorials!

In this repository, we've put together a collection of Jupyter notebooks aimed at teaching people who want to use Qiskit for writing quantum computing programs, and executing them on one of several backends (online quantum processors, online simulators, and local simulators). The online quantum processors are the IBM Quantum systems.

For our community-contributed tutorials, please check out the qiskit-community-tutorials repository.

The notebooks for these tutorials can be viewed here on GitHub. However, for the full experience, you will want to interact with them. The easiest way to do this is by logging into the IBM Quantum Experience, which lets you use Jupyter notebooks, including these tutorials, via the web.

Please refer to this installation guide for setting up Qiskit and the tutorials on your own machine (this is the recommended way).

To start seeing how Qiskit works, load up the start_here.ipynb notebook or view the tutorials in the Qiskit documentation.

In addition to serving up standalone notebooks, this repository also includes the infrastructure needed to build the tutorials into HTML documentation using Sphinx. Along with the Qiskit dependencies, building the documentation requires the following:

pip install Sphinx
pip install sphinx-rtd-theme
pip install nbsphinx

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

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

Qiskit IQX Tutorials is the work of many people who contribute to the project at different levels. If you use Qiskit, please cite as per the included BibTeX file.

Apache License 2.0