Tutorials

Five executed notebooks in notebooks/ take you from zero to running your own studies. Each states its audience and time budget; markdown outweighs code in all of them. Open them on GitHub, or run locally:

git clone https://github.com/TravisCao/qugrid && cd qugrid
uv sync --extra dev
uv run --with jupyterlab jupyter lab notebooks/

#	Notebook	Time	For whom	You leave with
01	01_hello_qugrid	15 min	everyone; zero quantum knowledge assumed	your first solved grid QUBO and the Result vocabulary: decoded, gap(), feasible, success_probability()
02	02_from_matpower_to_qubo	30 min	anyone with their own case data	the full encoding pipeline: MATPOWER columns → Network → hand-built QUBO with QUBOBuilder → what penalty weights do (both failure directions, demonstrated numerically)
03	03_quantum_optimization_101	45 min	power engineers who want to understand QAOA/VQE	the mechanics: amplitudes as island assignments, the (γ, β) landscape plot, distribution sharpening with depth, and why SA still wins at this scale
04	04_quantum_linear_solvers	30 min	anyone touching power flow	DC power flow as \(Ax=b\); HHL error anatomy (clock bits, fidelity vs relative error vs success probability); the hybrid Newton loop
05	05_qml_for_screening	30 min	ML-inclined researchers	N-1 screening as a classification task; quantum kernel vs RBF with the bandwidth experiment; QBM scenario generation

Suggested orders per background are in learning paths.