Speaker
Description
Galaxy clusters, the most massive bound structures in the Universe, continue to grow by accreting galaxies from filaments, groups, and even other clusters. As a result, galaxy evolution is influenced by interactions with its dynamic environments. To quantify this environmental impact, we analyze the surroundings of 50 massive clusters (up to 5xR200) from the CHANCES low redshift subsurvey (z<0.07). For this survey, we characterize the local environment using machine-learning classification and clustering techniques (e.g., KNN, HDBSCAN) to compute local galaxy densities and identify substructures. Additionally, to better understand the effects of these evolving environments on galaxy evolution and how they compare with the effects of the global environment, we extract morphological and interaction mechanism information from citizen science projects (e.g., Fishing for Jellyfish Galaxies). These projects can provide a good census of the physical mechanisms responsible for the pre- and post-processing of galaxies and help to improve the automatic classification of deeper finding images in future extragalactic research, such as those from JWST, LSST, etc.