An algorithm to build mock galaxy catalogues using MICE simulations

TL;DR

This paper introduces a new algorithm combining HOD and SHAM techniques to generate detailed mock galaxy catalogues from MICE simulations, accurately reproducing observed galaxy properties across luminosities.

Contribution

The novel method integrates HOD and SHAM to produce comprehensive mock catalogues that match observations at all luminosities, including faint galaxies.

Findings

Successfully reproduces the local galaxy luminosity function.

Accurately models galaxy clustering by luminosity and color.

Extends mock catalogue depth to fainter magnitudes.

Abstract

We present a method to build mock galaxy catalogues starting from a halo catalogue that uses halo occupation distribution (HOD) recipes as well as the subhalo abundance matching (SHAM) technique. Combining both prescriptions we are able to push the absolute magnitude of the resulting catalogue to fainter luminosities than using just the SHAM technique and can interpret our results in terms of the HOD modelling. We optimize the method by populating with galaxies friends-of-friends dark matter haloes extracted from the Marenostrum Institut de Ci\`{e}ncies de l'Espai (MICE) dark matter simulations and comparing them to observational constraints. Our resulting mock galaxy catalogues manage to reproduce the observed local galaxy luminosity function and the colour-magnitude distribution as observed by the Sloan Digital Sky Survey. They also reproduce the observed galaxy clustering properties as a function of luminosity and colour. In order to achieve that, the algorithm also includes scatter in the halo mass - galaxy luminosity relation derived from direct SHAM and a modified NFW mass density profile to place satellite galaxies in their host dark matter haloes. Improving on general usage of the HOD that fits the clustering for given magnitude limited samples, our catalogues are constructed to fit observations at all luminosities considered and therefore for any luminosity subsample. Overall, our algorithm is an economic procedure of obtaining galaxy mock catalogues down to faint magnitudes that are necessary to understand and interpret galaxy surveys.