Mock galaxy lightcone for photometric surveys
Photometric surveys have been important in establishing our current understanding of how galaxies form and evolve. Synthetic galaxy catalogues are crucial to optimally exploit their data, in particular for the case of photometric surveys that combine broad-band and narrow-band filters.
In order to build realistic catalogues for photometric surveys, there are several requirements. First, one requires a galaxy formation model that predicts all the relevant observable properties of galaxies, such as position, redshift, metallicity, stellar mass, or star formation rate. Second, it is important to include emission lines from star-forming regions. Although lines contribute in a relatively minor way to broad-band magnitudes, they can dominate the total flux in narrow and medium bands. Third, it is necessary to project the light and spatial distribution of mock galaxies onto the observer’s frame of reference. This, the so-called lightcone, is a crucial ingredient since a given narrow band can receive contributions from multiple emission lines at different redshifts.
In Izquierdo-Villalba et al. (2019) we present a new procedure to generate a synthetic galaxy lightcones, specially designed for narrow-band surveys. We employ state-of-the-art theoretical galaxy formation models applied to a large N-body simulation to predict the properties and clustering of galaxies. We improve these results with a model for the nebular emission from star-forming regions considering the contribution of nine different transition lines. The properties of these lines are computed separately for each mock galaxy based on its predicted star formation and metallicity. Additionally, we embed the lightcone building procedure inside the galaxy formation modelling, allowing us to minimize the time-discreteness effects. As an application of our lightcone construction, we have generated catalogues for the photometry of the ongoing J-PLUS photometric survey. Our J-PLUS catalogues are publicly released here.
We have employed the L-Galaxies SAM code, in the variant presented by Guo et al. (2011). The dark matter merger trees used are the ones extracted form the Millennium simulation. Given the halo mass resolution, we expect converged properties and abundance for galaxies with stellar masses above ~108 M⊙/h. The 500 Mpc/h side-length of the Millennium simulation is not always able to encompass the full volume, or redshift range, of observational surveys. Thus, to cover the relevant regions, we take advantage of its periodic boundary conditions and replicate the simulated box 8 times in each coordinate direction. This corresponds to a maximum redshift of z~3, and will also allow us to incorporate high-z ELGs as potential contamination for low-z ELGs. For convenience, we place the observer at the origin of the first replication and define the extent of the lightcone as the angular size of 1000 Mpc/h at z~1. This ensures that no more than two repetitions are required to represent the cosmic structure in any redshift shell up to z~1.
In order to include the contribution of emission lines to the predicted photometry of our mock galaxies, we follow the model described in Orsi et al. (2014). Specifically, we consider the contribution of 9 different lines: Lyα (1216Å), Hβ (4861Å), Hα (6563Å), [OII] (3727Å, 3729Å), [OI] (4959Å, 5007Å), [NeIII] (3870Å), [OI] (6300Å), [NII] (6548Å, 6583Å), and [SII] (6717Å, 6731Å), [CII] (15800Å) and [NII] (20500Å), which are those we expect to contribute most significantly to the rest-frame optical wavelength.
In Izquierdo-Villalba et al. (2019) we presented various tests to validate our lightcone construction. Galaxy photometry has been tested with the galaxy number counts in ugriz SDSS broad bands. In the case of galaxy spatial distribution, we have compared the clustering of g selected galaxies with the work of Favole et al. (2016). In both cases the agreement is good.
We refer the reader to Izquierdo-Villalba et al. (2019) for a detailed explanation of the mock construction.
How to cite
If you have used this data in your paper, please cite the following papers:
If you have any issue or doubt write to email@example.com.