September 7, 2019

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A collection of Jupyter notebooks showing how to use Qiskit that is synced with the IBM Q Experience

repo name Qiskit/qiskit-iqx-tutorials
repo link
language Jupyter Notebook
size (curr.) 129653 kB
stars (curr.) 1200
created 2017-08-03
license Apache License 2.0

Qiskit IQX Tutorials


Welcome to the Qiskit IQX 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 Q devices.

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


The notebooks for these tutorials can be viewed here on GitHub…but for the full experience, you’ll 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).


We’ve collected a core reference set of notebooks in this section outlining the features of Qiskit. We will be keeping them up to date with the latest Qiskit version.

  • Basics is for those who are getting started.
  • Terra is for those who want to study circuits.
  • Aer is for those who want to simulate quantum circuits.
  • Ignis is for those who want to study noise.
  • Aqua is for those who want to develop applications on noisy quantum devices.

To go through the Qiskit examples, load up the start_here.ipynb notebook and start seeing how Qiskit works.

Contribution Guidelines

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.

Authors and Citation

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

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