A study of jellyfish galaxies in cosmological simulations

Abstract

Galaxy transformations in cluster environments represent one of the key processes driving galaxy evolution. Among these transformations, ram pressure stripping (RPS) plays a crucial role in shaping galaxies and their gas content as they fall into clusters. However, we still don’t fully understand the efficiency and consequences of RPS in galaxy evolution. This study investigates the evolution of jellyfish galaxies in cluster environments using IllustrisTNG simulations and citizen science classifications. Our sample is divided into two distinct populations: high-confidence and medium-confidence jellyfish galaxies, based on their morphological features as classified by volunteers. Jellyfish galaxies, characterized by their distinctive gas tails shaped by RPS, provide unique insights into environmental processes affecting galaxy evolution. Through the analysis of high-confidence galaxies, we find these systems are predominantly recent infallers within R200, exhibiting ongoing star formation and broad color distributions indicative of early quenching. In contrast, medium-confidence galaxies show lower gas masses, redder colors, and more advanced quenching, reflecting prolonged gas depletion. The temporal evolution of gas mass reveals rapid stripping in high-confidence galaxies, with up to 37% of their gas removed within 0.5 Gyr post-infall. Our results demonstrate that citizen science enables efficient identification of jellyfish morphologies across large datasets, highlighting its value in addressing challenges posed by big data in modern astrophysics while advancing our understanding of environmental processes in galaxy evolution.