Reconstructing orbits of galaxies in extreme regions (roger v2.0): an extension to intermediate mass systems
Roger v2.0 is an updated orbital classification code for galaxies in galaxy groups and clusters. It improves robustness by adding host halo mass as a third input parameter to analyze projected phase-space coordinates. The system classifies galaxies into five distinct orbital types, using machine learning models like KNN and Random Forests for prediction.