Characterising the target selection pipeline for the Dark Energy Spectroscopic Instrument Bright Galaxy Survey

TL;DR

This paper details the development of a reliable galaxy target selection pipeline for the DESI Bright Galaxy Survey, addressing key issues like star-galaxy separation and contamination, and validating the catalogue's completeness and clustering performance.

Contribution

It introduces a new target selection method using Gaia photometry and implements masks to reduce spurious objects, improving the reliability of the galaxy catalogue for DESI BGS.

Findings

Achieved a 7% suppression of target density in high stellar density regions.

Validated the catalogue's clustering by comparison with mock and SDSS data.

Assessed the completeness and systematic effects in the target selection process.

Abstract

We present the steps taken to produce a reliable and complete input galaxy catalogue for the Dark Energy Spectroscopic Instrument (DESI) Bright Galaxy Survey (BGS) using the photometric Legacy Survey DR8 DECam. We analyse some of the main issues faced in the selection of targets for the DESI BGS, such as star-galaxy separation, contamination by fragmented stars and bright galaxies. Our pipeline utilizes a new way to select BGS galaxies using Gaia photometry and we implement geometrical and photometric masks that reduce the number of spurious objects. The resulting catalogue is cross-matched with the Galaxy And Mass Assembly (GAMA) survey to assess the completeness of the galaxy catalogue and the performance of the target selection. We also validate the clustering of the sources in our BGS catalogue by comparing with mock catalogues and the Sloan Digital Sky Survey (SDSS) data. Finally, the robustness of the BGS selection criteria is assessed by quantifying the dependence of the target galaxy density on imaging and other properties. The largest systematic correlation we find is a 7 per cent suppression of the target density in regions of high stellar density.