This package makes it practical for physics researchers to apply modern ML techniques (classification, object detection) to quantum gas experiments without building infrastructure from scratch.
Q-GAIN is a Python package that combines machine learning with physics-informed analysis for cold-atom experiments. It provides pre-built tools for classifying images, detecting objects, and analyzing quantum gas systems like Bose-Einstein condensates, with a modular workflow that connects data loading, ML-based feature detection, and physics analysis.