Testing Subhalo Abundance Matching in Cosmological Smoothed Particle Hydrodynamics Simulations
Vimal Simha, David Weinberg, Romeel Dave, Mark Fardal, Neal Katz,, Benjamin D. Oppenheimer

TL;DR
This study evaluates the accuracy of subhalo abundance matching (SHAM) in cosmological hydrodynamical simulations, demonstrating its effectiveness in reproducing galaxy distributions and clustering, with some limitations related to satellite galaxy mass loss.
Contribution
The paper provides a detailed assessment of SHAM's performance in SPH simulations, including the impact of galaxy feedback processes and comparison with collisionless N-body results.
Findings
SHAM accurately reproduces median stellar mass-halo mass relations.
SHAM recovers galaxy clustering within 10-15% accuracy.
Satellite galaxy mass loss affects halo occupation predictions.
Abstract
Subhalo abundance matching (SHAM) is a technique for populating simulated dark matter distributions with galaxies, assuming a monotonic relation between a galaxy's stellar mass or luminosity and the mass of its parent dark matter halo or subhalo. We examine the accuracy of SHAM in two cosmological SPH simulations, one of which includes momentum-driven winds. The SPH simulations indeed show a nearly monotonic relation between stellar mass and halo mass provided that, for satellite galaxies, we use the mass of the subhalo at the epoch when it became a satellite. In each simulation, the median relation for central and satellite galaxies is nearly identical, though a somewhat larger fraction of satellites are outliers. SHAM-assigned masses (at z=0-2), luminosities (R-band at z=0), or star formation rates (at z=2) have a 68% scatter of 0.09-0.15 dex relative to the true simulation values.…
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