maggie: Models and Algorithms for Galaxy Groups, Interlopers and Environment

Abstract

Combining our knowledge of halo structure and internal kinematics from cosmological dark matter simulations and the distribution of halo interlopers in projected phase space measured in cosmological galaxy simulations, we develop MAGGIE, a prior-and halo-based, probabilistic, abundance matching (AM) grouping algorithm for doubly complete subsamples (in distance and luminosity) of flux-limited samples. We test MAGGIE-L and MAGGIE-M (in which group masses are derived from AM applied to the group luminosities and stellar masses, respectively) on groups of at least three galaxies extracted from a mock Sloan Digital Sky Survey Legacy redshift survey, incorporating realistic observational errors on galaxy luminosities and stellar masses. In comparison with the optimal Friends-of-Friends (FoF) group finder, groups extracted with MAGGIE are much less likely to be secondary fragments of true groups; in primary fragments, its galaxy memberships (relative to the virial sphere of the realspace group) are much more complete and usually more reliable, and its masses are much less biased and usually with less scatter, as are its group luminosities and stellar masses (computed in MAGGIE using the membership probabilities as weights). FoF outperforms MAGGIE only for high-mass clusters: for the reliability of the galaxy population and the dispersion of its total mass. In comparison with our implementation of the Yang et al. group finder, MAG-GIE reaches much higher completeness and slightly lower group fragmentation and dispersion on group total masses, luminosities and stellar masses, but slightly greater bias in the latter two and lower reliabilities. MAGGIE should therefore lead to sharper trends of environmental effects on galaxies and more accurate mass/orbit modelling.

Assessing colour-dependent occupation statistics inferred from galaxy group catalogues

“…in the vain of Botzler et al 2004;Li & Yee 2008;Jian et al 2014;Duarte & Mamon 2014b). Given some model, it is possible to assign probabilities that individual galaxies reside in a common group-currently this information is explicitly ignored in (Yang et al , 2007.…”

“…Given some model, it is possible to assign probabilities that individual galaxies reside in a common group-currently this information is explicitly ignored in (Yang et al , 2007. During the final stages of preparation of this manuscript Duarte & Mamon (2014b) have explicitly retained and used probabilities of group membership in the formulation of a new group finder, MAGGIE. While it would be very interesting to investigate whether MAGGIE, or another probabilistic approach to the the grouping problem, alleviates some of the issues investigated here, we leave this to future work.…”

“…Tinker et al (2011) note that impurities in satellite and central galaxy samples in a group catalogue will bias the quenched fractions measured from group catalogues,and Hou et al (2014) speculate that group membership contamination may influence the measurements of star formation in galaxy groups as a function of environment. Duarte & Mamon (2014b) recently developed a method to take into account the uncertainties in the group finding process; however, it is unclear if this will improve the situation. In this paper, we investigate, in detail, the ability of group finders to recover galaxy(-group) properties as a function halo properties, and how group catalogue failures skew measurements.…”

Galaxy groups in the low-redshift Universe

“…Lu et al 2016). Similarly, Duarte & Mamon (2015) adopted an iterative group membership assignment algorithm but in a probabilistic way using galaxy distribution statistics extracted from N-body simulation. An important step in the halo-based group finder is the use of a halo-mass proxy to assign halo masses to tentative groups/clusters in the grouping process.…”

GalWeight Application: A Publicly Available Catalog of Dynamical Parameters of 1800 Galaxy Clusters from SDSS-DR13, (GalWCat19)

“…It uses galaxy distances derived from spectroscopic or photometric redshifts as the main basis of grouping. Another group of cluster finding methods are halo-based group finders (Yang et al 2005(Yang et al , 2007Duarte & Mamon 2015). These methods assume some criteria to identify galaxies which belong to the same dark matter halo.…”