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A demonstrator for the Sequoia End-to-End project which shows how scenario-based route planning to safeguard automotive driving functions can be implemented to run on a quantum computer

The demonstrator shows the time evolution of a small network with failures.

End-to-end demonstrator for quantum optimization of charging schedules.

This notebook illustrates using the Quantum Approximate Optimization Algorithm (QAOA) to find optimized configurations for feature models with attributed costs on a quantum computer.

Solving a combinatorial optimization problem with a hybrid quantum-classical algorithm.

An alternative problem encoding for QAOA is used to accelerate cost function computation

Simulation env based on Brax / MuJoCo for robotic assembly tasks.

matplotlib: plotting with Python