Abstract
ABSTRACT Subhalo abundance matching (SHAM) is a popular technique for assigning galaxy mass or luminosity to haloes produced in N-body simulations. The method works by matching the cumulative number functions of the galaxy and halo properties, and is therefore sensitive both to the precise definitions of those properties and to the selection criteria used to define the samples. Further dependence follows when SHAM parameters are calibrated with galaxy clustering, which is known to depend strongly on the manner in which galaxies are selected. In this paper we introduce a new parametrization for SHAM and derive the best-fitting SHAM parameters as a function of various properties of the selection of the galaxy sample and of the photometric definition, including Sérsic versus Petrosian magnitudes, stellar masses versus r-band magnitudes, and optical (Sloan Digital Sky Survey) versus $\mathrm{H}\, \small {\rm I}$ (ALFALFA) selection. In each case we calculate the models’ goodness-of-fit to measurements of the projected two-point galaxy correlation function. In the optically selected samples we find strong evidence that the scatter in the galaxy–halo connection increases towards the faint end, and that AM performs better with luminosity than stellar mass. The SHAM parameters of optically and $\mathrm{H}\, \small {\rm I}$-selected galaxies are mutually exclusive, with the latter suggesting the importance of properties beyond halo mass. We provide best-fitting parameters for the SHAM galaxy–halo connection as a function of each of our input choices, extending the domain of validity of the model while reducing potential systematic error in its use.
Highlights
Our best tool to understand the growth of structure in the Universe is simulation of dark matter halo formation and evolution
By splitting each catalogue into subsamples defined by lower and upper thresholds of luminosity or mass we can address whether the halo proxy shows any dependence on these quantities, which of them is best-suited for subhaloes abundance matching (SHAM), and how the best-fitting parameters respond to the photometric reduction
Based on a simple qualitative comparison we note that the clustering of the ALFALFA × Nasa Sloan Atlas (NSA) catalogue shows only marginal dependence on H I mass, we find a stronger dependence on the baryonic mass
Summary
Our best tool to understand the growth of structure in the Universe is simulation of dark matter halo formation and evolution. While cosmological hydrodynamical simulations have increased greatly in sophistication in the past decade, the complexity of baryonic processes means that simulations of the gravitational physics of dark matter only (N-body simulations) remain the most robust, with broad consensus on the resulting halo population across the range of algorithms that have been used (Navarro, Frenk & White 1997; Knebe et al 2011; Schneider et al 2016). To connect such simulations to observations, empirical and semi-analytic models have been developed to associate galaxies with the simulated haloes and track the coevolution of the two over cosmic time. This suggests that SHAM encapsulates important physics regarding the processes of galaxy formation, and makes it useful for cosmological studies that require the galaxy–halo connection as input (e.g. Reddick et al 2014)
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