Numerical resolution limits on subhalo abundance matching
Qi Guo, Simon White

TL;DR
This paper investigates the numerical resolution limits of subhalo abundance matching in cosmological simulations, highlighting how resolution affects galaxy clustering predictions and proposing methods to improve convergence.
Contribution
It compares different simulation resolutions to determine the minimum subhalo mass for reliable galaxy clustering analysis and discusses the benefits of tracking orphan galaxies.
Findings
Correlation statistics converge within 20% for subhalos with at least 1000 particles at infall.
Higher resolution simulations improve the accuracy of galaxy clustering predictions.
Tracking orphan galaxies extends the reliable mass range for comparison with observations.
Abstract
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 distinct self-bound subhalo with a luminosity which is a monotonically increasing function of the maximum mass (or circular velocity) attained over the subhalo's earlier history. Galaxy and subhalo properties are linked by matching model and observed luminosity functions. Simulated structures can then be compared in detail with observation, for example, through galaxy correlation statistics, group catalogues, or galaxy-galaxy lensing. Robust astrophysical conclusions can be drawn from such a comparison only on scales which are unaffected by the numerical limitations of the simulation. Here we compare results for the Millennium Simulation (MS) with…
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