Combining friend-of-friend and halo-based algorithms for the identification of galaxy groups

Abstract

Context. Galaxy groups provide the means for a great diversity of studies that contribute to a better understanding of the structure of the universe on a large scale and allow the properties of galaxies to be linked to those of the host halos. However, the identification of galaxy systems is a challenging task and therefore it is necessary to improve the techniques involved as much as possible. Aims. In view of the large present and forthcoming galaxy catalogues, we propose, implement, and evaluate an algorithm that combines the two most popular techniques used to identify galaxy systems. The algorithm can be easily applied to any spectroscopic galaxy catalogue, but here we demonstrate its use on the Sloan Digital Sky Survey. Methods. Assuming that a galaxy group is a gravitationally bounded system that has at least one bright galaxy, we begin by identifying groups with a Friends-Of-Friends algorithm adapted to fit this definition. In view of the shortcomings of this method, particularly the lack of ability to identify low-number groups, and consequently the inability to study the occupation of halos throughout the mass range, we improve it by adding a halo-based procedure. To assess the performance, we construct a mock catalogue from a semianalytical model to compare the groups identified using our method with those obtained from the simulation. Results. The comparison of groups extracted using our method with those of a mock catalogue shows that the proposed algorithm provides excellent results. The modifications introduced to the Friends-Of-Friends algorithm in the first part of the procedure to fit the adopted group definition gave reliable groups. Furthermore, incorporation of the halo-based method reduces the interlopers while more accurately reproducing the number of galaxies per group. As a specific application, we use the algorithm to extract groups from the Sloan Digital Sky Survey.

Compact Groups of Galaxies in Sloan Digital Sky Survey and LAMOST Spectral Survey. I. The Catalogs

“…Many samples of galaxy groups based on halo models have been established in various redshift surveys: e.g., Yang et al (2005) from the 2dFGRS; Weinmann et al (2006), Yang et al (2007Yang et al ( , 2012, Muñoz-Cuartas & Müller (2012), and Rodriguez & Merchán (2020) from the SDSS; Lu et al (2016) from the 2MRS; Lim et al (2017) from the 2MRS, 2dFGRS, 6dFGRS, and SDSS. Meanwhile, different CG catalogs also have been constructed (e.g., Barton et al 1996;Lee et al 2004;Mc-Connachie et al 2009;Díaz-Giménez et al 2012;Sohn et al 2016;Díaz-Giménez et al 2018).…”

The Subaru HSC weak lensing mass-observable scaling relations of spectroscopic galaxy groups from the GAMA survey

“…We also compare our results with a recent study of (Gonzalez et al 2021) who identify groups using spectroscopic galaxies from the SDSS-DR12 survey (Rodriguez & Merchán 2020) and carry out a weak lensing study using a heterogenous collection of shear catalogues -CFHTLenS, CS82, RCSLens and KiDS. The green data points represent their median halo-mass constraints with 1𝜎 error bars at a median velocity dispersion value in the corresponding bin.…”

“…Also, these methods heavily depend on the underlying assumptions -dynamical methods require a virialized system while X-ray estimation needs a hydrostatic equilibrium of intracluster gas (see e.g., Kettula et al 2013;Pearson et al 2015;Foëx et al 2017). An alternate approach for estimating halo masses for group scale objects is halo abundance matching, by measuring the abundance of galaxy groups by their group luminosity or total group stellar mass content and connecting it to the halo mass function (see e.g., Yang et al 2007;Rodriguez & Merchán 2020;Yang et al 2021). These estimates depend sensitively upon the assumed input cosmology.…”

The galaxy size–halo mass scaling relations and clustering properties of central and satellite galaxies

“…In order to identify central and satellite galaxies in the SDSS sample described above, a galaxy group catalogue is built using the galaxy group finder presented in Rodriguez & Merchán (2020), which combines both the FOF and the halo-based methods. Assuming that 2 Available on the IllustrisTNG database.…”

“…Several methods have been proposed to extract clusters from massive galaxy surveys, but the most widely used are the friends-of-friends (FOF; Huchra & Geller 1982) and halo-based methods (Yang et al 2005). In a recent work, Rodriguez & Merchán (2020) present a technique that combines these two methods in order to efficiently identify groups in survey data.…”