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Constraint-Driven QAOA Design

A tutorial by Aqarios GmbH

Link to Tutorial Slides

This tutorial is composed of six notebooks that will teach you

  • 01_QAOA: The basics of the Quantum Approximate Optimization Algorithm (QAOA)
  • 02_PenaltyTerms: Reformulating constriants into objectives in an automatic manner.
  • 03_XYMixers: Automatic Handling of One-Hot Constraints via XY-Mixers
  • 04_Aqarios_Luna: Using the Aqarios LunaSolve platform for solving your optimization problems. See how FlexQAOA does constraint handling automatically.
  • 05_Benchmarking: Best Practices in Benchmarking Quantum Optimization Algorithms
  • 06_ModelExtension: Getting to know more capabilities of FlexQAOA.

We hope you have fun exploring this tutorial! 🚀

Python Setup

Use a python version >=3.11.

We recommend using uv for dependency management and installation (astral/uv). Simply run

uv sync

and every dependency will be installed.

Otherwise, you can use your preferred dependency management, e.g. pip

pip install -r requirements.txt
pip install -e .

Luna Registration

To register to Luna, please visit app.aqarios.com. Plese complete the steps you are ask and log into the platform.

You should be able to see the Luna API Key field on the top right. Copy the key and put it into the .env file.

echo "LUNA_API_KEY=<THE_API_KEY>" > .env

💡 Ready to dive deeper?

Explore more tutorials, documentation, and resources to accelerate your journey

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💬 Need Help?

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Tutorial provided by Aqarios GmbH | © 2025 Aqarios GmbH | Made with ❤️ for developers

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