use for quantum machine learning engineering in this repository, especially when the user asks about pps-based qaoa optimization, surrogate compilation or evaluation, exact-vs-pps backend tradeoffs, scaling behavior, circuit design, training stability, memory or ddp issues, artifact interpretation, or experiment planning. this is a repo-aware quantum engineering skill for implementation, debugging, optimization, and experiment design across quantum machine learning workflows, not limited to qgan. do not trigger for pure data analysis or manuscript-only editing.