Year: 2018
Type: article
Abstract: Identifying galaxies in hydrodynamical simulations is a difficult task, particularly in regions of high density such as galaxy groups and clusters. We present a new scale-free, shape-independent algorithm to robustly and accurately identify galaxies in simulations, implemented within the phase-space halo-finder code velociraptor. This is achieved by using the full phase-space dispersion tensor for particle assignment and an iterative adjustment of search parameters, which help us overcome common structure-finding problems. We apply our improved method to the Horizon-AGN simulation and compare galaxy stellar masses (M*), star formation rates (SFRs), and sizes with the elaborate configuration-space halo-finder halomaker. Galaxies living in haloes with >1 galaxy are the most affected by the shortcomings of real-space finders, with their mass, SFR, and size being >2 times larger (smaller) in the case of host (satellite) galaxies. Thus, our ability to measure minor/major merger rates and disentangle environmental effects in simulations can be generally hindered if the identification of galaxies is not treated carefully. Though large systematic differences are obtained on a one-to-one basis, the overall galaxy stellar mass function, the SFR function, and the mass–size relations are not greatly affected. This is due to isolated galaxies being the most abundant population, dominating broad statistics.
Authors: Rodrigo Cañas, Pascal J Elahi, Charlotte Welker, Claudia del P Lagos, Chris Power, Yohan Dubois, Christophe Pichon
Institutions: The University of Western Australia, ASTRO-3D, ARC Centre of Excellence for All-sky Astrophysics, International Centre for Radio Astronomy Research, Korea Institute for Advanced Study, Centre National de la Recherche Scientifique, Institut d'Astrophysique de Paris, Royal Observatory, Université Pierre-et-Marie-Curie, University of Edinburgh
Language: English
Subfield: Astronomy and Astrophysics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2895928534
