Published in

Oxford University Press, Monthly Notices of the Royal Astronomical Society, 4(502), p. 4858-4876, 2021

DOI: 10.1093/mnras/stab231

Links

Tools

Export citation

Search in Google Scholar

Mock light-cones and theory friendly catalogues for the CANDELS survey

This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

Full text: Unavailable

Green circle
Preprint: archiving allowed
Green circle
Postprint: archiving allowed
Green circle
Published version: archiving allowed
Data provided by SHERPA/RoMEO

Abstract

ABSTRACT We present mock catalogues created to support the interpretation of the Cosmic Assembly Near-IR Deep Extragalactic Legacy Survey (CANDELS). We extract haloes along past light-cones from the Bolshoi Planck dissipationless N-body simulations and populate these haloes with galaxies using two different independently developed semi-analytic models of galaxy formation and the empirical model universemachine. Our mock catalogues have geometries that encompass the footprints of observations associated with the five CANDELS fields. In order to allow field-to-field variance to be explored, we have created eight realizations of each field. In this paper, we present comparisons with observable global galaxy properties, including counts in observed frame bands, luminosity functions, colour–magnitude distributions and colour–colour distributions. We additionally present comparisons with physical galaxy parameters derived from SED fitting for the CANDELS observations, such as stellar masses and star formation rates. We find relatively good agreement between the model predictions and CANDELS observations for luminosity and stellar mass functions. We find poorer agreement for colours and star formation rate distributions. All of the mock light-cones as well as curated ‘theory friendly’ versions of the observational CANDELS catalogues are made available through a web-based data hub.