Related papers: Modeling Redshift-Space Clustering with Abundance …
We develop an extension of subhalo abundance matching (SHAM) capable of accurately reproducing the real and redshift-space clustering of galaxies in a state-of-the-art hydrodynamical simulation. Our method uses a low-resolution gravity-only…
With the advent of several galaxy surveys targeting star-forming galaxies, it is important to have models capable of interpreting their spatial distribution in terms of astrophysical and cosmological parameters. To address this need, we…
We model the luminosity-dependent projected and redshift-space two-point correlation functions (2PCFs) of the Sloan Digital Sky Survey (SDSS) DR7 Main galaxy sample, using the halo occupation distribution (HOD) model and the subhalo…
Subhalo abundance matching (SHAM) is a commonly used framework for modeling the galaxy-halo connection. Yet, its standard implementation has difficulty reproducing the observed galaxy clustering with high accuracy (e.g.,…
We use the {\sc Illustris TNG300} magneto-hydrodynamic simulation, the {\sc SAGE} semi-analytical model, and the subhalo abundance matching technique (SHAM) to examine the diversity in predictions for galaxy assembly bias (i.e. the…
We present a first application of the subhalo abundance matching (SHAM) method to describe the redshift-space clustering of galaxies including the non-linear redshift-space distortion, i.e., the Fingers-of-God. We find that the standard…
We place constraints on the matter density of the Universe and the amplitude of clustering using measurements of the galaxy two-point correlation function from the Sloan Digital Sky Survey (SDSS). We generate model predictions for different…
SubHalo Abundance Matching (SHAM) is an empirical method for constructing galaxy catalogues based on high-resolution $N$-body simulations. We apply SHAM on the UNIT simulation to simulate SDSS BOSS/eBOSS Luminous Red Galaxies (LRGs) within…
Galaxy clustering on small scales is significantly under-predicted by sub-halo abundance matching (SHAM) models that populate (sub-)haloes with galaxies based on peak halo mass, $M_{\rm peak}$. SHAM models based on the peak maximum circular…
Recent studies emphasize that an empirical relation between the stellar mass of galaxies and the mass of their host dark matter subhaloes can predict the clustering of galaxies and its evolution with cosmic time. In this paper we study the…
We use subhalo abundance matching (SHAM) to model the stellar mass function (SMF) and clustering of the Baryon Oscillation Spectroscopic Survey (BOSS) "CMASS" sample at $z\sim0.5$. We introduce a novel method which accounts for the stellar…
Models of the galaxy-halo connection are needed to understand both galaxy clusters and large scale structure. To make said models, we need a robust method that assigns galaxies to halos and matches the observed and simulated stellar-halo…
Subhalo abundance matching (SHAM) is a widely-used method to connect galaxies with dark matter structures in numerical simulations. SHAM predictions agree remarkably well with observations, yet they still lack strong theoretical support. We…
Subhalo abundance matching (SHAM) inserts galaxies into dark matter only simulations of the growth of cosmic structure in a way that requires minimal assumptions about galaxy formation. A galaxy is placed at the potential minimum of each…
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…
Combining galaxy clustering information from regions of different environmental densities can help break cosmological parameter degeneracies and access non-Gaussian information from the density field that is not readily captured by the…
We analyse a catalogue of simulated clusters within the theoretical framework of the Spherical Collapse Model (SCM), and demonstrate that the relation between the infall velocity of member galaxies and the cluster matter overdensity can be…
We present an optimisation method for the assignment of photometric galaxies into a chosen set of redshift bins. This is achieved by combining simulated annealing, an optimisation algorithm inspired by solid-state physics, with an…
The spatial distribution of massive and luminous galaxies have provided important constraints on the fundamental cosmological parameters and physical processes governing galaxy formation. In this work, we construct and compare independent…
In simulation-based models of the galaxy-halo connection, theoretical predictions for galaxy clustering and lensing are typically made based on Monte Carlo realizations of a mock universe. In this paper, we use Subhalo Abundance Matching…