| Abstract: Galaxy groups are an important link between individual galaxies and the large scale structure of the Universe. Most galaxies do not live in isolation but reside in groups and clusters, which trace the underlying dark matter halos. Identifying galaxy groups is therefore crucial for understanding galaxy formation and evolution, halo occupation, and the growth of cosmic structure.
However, identifying galaxy groups in modern spectroscopic surveys is challenging. Surveys like the Dark Energy Spectroscopic Instrument (DESI) use fiber-fed instruments, which cannot observe very close galaxy pairs simultaneously due to fiber collision limits. This leads to missing galaxies in dense regions, causing biased group membership, underestimated group richness, and misclassification of central and satellite galaxies. Many traditional group finding algorithms are not designed to properly handle these effects.
In this poster, we focus on evaluating and improving galaxy group finders for modern spectroscopic surveys, with special attention to DESI. We study several existing approaches, with particular emphasis on NESSIE, a recently developed galaxy group finder. NESSIE is based on a Friends-of-Friends approach, where galaxy groups are identified using adaptive linking lengths, taking the sky coordinates and redshift of the galaxies as input.
To address fiber collision effects, we test the group finder using realistic DESI mock catalogues that include survey geometry, selection effects, and fiber collision information. By comparing recovered groups with true halo properties in simulations, we quantify the impact of fiber collisions on group completeness and purity and develop improvements to reduce biases caused by missing galaxies.
Thus this poster aims to produce validated galaxy group catalogues tailored to DESI systematics, enabling robust studies of galaxy environments and large-scale structure. |
