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IBM Quantum's open-source content
IBM provides a wealth of quantum computing learning material — all open source under CC BY-SA 4.0:
- Learning — Structured courses from quantum basics to advanced topics
- Tutorials — 40+ tutorials on transpilation, error mitigation, and more
- Documentation — Guides and API reference for Qiskit
- Source repo — All content on GitHub
Their Quantum Platform is always up-to-date and well-designed — the best place for reading, learning, and reference.
What this project adds
IBM's Qiskit documentation is open source (CC BY-SA 4.0), but their web application is not. doQumentation adds an open-source frontend with live code execution, automatic credential injection, and simulator mode.
Deployable anywhere — from GitHub Pages to Docker to RasQberry. See all features.
Getting started
New to quantum computing? Start with the course. Already familiar with Qiskit? Jump into a tutorial or guide.
No IBM Quantum account? Enable Simulator Mode in Settings to run all code without signing up.
Code execution
Click Run on any code block. The first click starts a free Jupyter kernel via Binder (1–2 min). After that, runs are instant.
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Simulator Mode (no account needed) — Enable Simulator Mode to run all notebooks with AerSimulator or noise-model FakeBackends. Zero setup required.
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IBM Quantum Hardware — Enter your API token and CRN in Settings once — credentials are auto-injected on every run. Create a free account if you don't have one.
Available execution backends
Every tutorial has executable code blocks. Click Run to execute them using one of three backends:
- Binder (default on GitHub Pages) — Free remote Jupyter kernel via mybinder.org
- Local Jupyter (Docker / RasQberry) — Connects to the local Jupyter server with Qiskit pre-installed
- Custom server — Point to any Jupyter endpoint in Settings
Deployment options
doQumentation is available as:
- GitHub Pages — Static site with Binder for remote code execution
- Docker — Full stack locally, offline capable
- RasQberry — Self-hosted on Raspberry Pi with local Jupyter kernel
Run locally with Podman / Docker
Install Podman Desktop or Docker Desktop (Mac / Windows / Linux), then run:
# Full stack: site + Jupyter + Qiskit (~3 GB)
podman run -p 8080:80 -p 8888:8888 ghcr.io/janlahmann/doqumentation:jupyter
Open http://localhost:8080 — code execution works locally, no Binder wait time.
For a lightweight version without local code execution (~60 MB):
# Static site only — code execution still works via Binder
podman run -p 8080:80 ghcr.io/janlahmann/doqumentation:latest
Using Docker instead? Just replace podman with docker — the commands are identical. Images are multi-arch (linux/amd64 + linux/arm64), so Apple Silicon Macs work natively.