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Register a new userPreliminary Target Selection for the DESI Bright Galaxy Survey (BGS)
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Omar Ruiz-Macias Mr.
Publication date
2020
fields
Physics
and research's language is
English
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The Dark Energy Spectroscopic Instrument (DESI) will execute a nearly magnitude-limited survey of low redshift galaxies ($0.05 leq z leq 0.4$, median $z approx 0.2$). Clustering analyses of this Bright Galaxy Survey (BGS) will yield the most precise measurements to date of baryon acoustic oscillations and redshift-space distortions at low redshift. DESI BGS will comprise two target classes: (i) BRIGHT ($r<19.5$~mag), and (ii) FAINT ($19.5<r<20$~mag). Here we present a summary of the star-galaxy separation, and different photometric and geometrical masks, used in BGS to reduce the number of spurious targets. The selection results in a total density of $sim 800$ objects/deg$^2$ for the BRIGHT and $sim 600$ objects/deg$^2$ for the FAINT selections.A full characterization of the BGS selection can be found in Ruiz-Macias et al. (2020).
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The DESI Milky Way Survey (MWS) will observe $ge$8 million stars between $16 < r < 19$ mag, supplemented by observations of brighter targets under poor observing conditions. The survey will permit an accurate determination of stellar kinematics and population gradients; characterize diffuse substructure in the thick disk and stellar halo; enable the discovery of extremely metal-poor stars and other rare stellar types; and improve constraints on the Galaxys 3D dark matter distribution from halo star kinematics. MWS will also enable a detailed characterization of the stellar populations within 100 pc of the Sun, including a complete census of white dwarfs. The target catalog from the preliminary selection described here is public.
The DESI survey will observe more than 8 million candidate luminous red galaxies (LRGs) in the redshift range $0.3<z<1.0$. Here we present a preliminary version of the DESI LRG target selection developed using Legacy Surveys Data Release 8 $g$, $r$, $z$ and $W1$ photometry. This selection yields a sample with a uniform surface density of ${sim},600$ deg$^{-2}$and very low predicted stellar contamination and redshift failure rates. During DESI Survey Validation, updat
DESI will precisely constrain cosmic expansion and the growth of structure by collecting $sim$35 million redshifts across $sim$80% of cosmic history and one third of the sky to study Baryon Acoustic Oscillations (BAO) and Redshift Space Distortions (RSD). We present a preliminary target selection for an Emission Line Galaxy (ELG) sample, which will comprise about half of all DESI tracers. The selection consists of a $g$-band magnitude cut and a $(g-r)$ vs. $(r-z)$ color box, which we validate using HSC/PDR2 photometric redshifts and DEEP2 spectroscopy. The ELG target density should be $sim$2400 deg$^{-2}$, with $sim$65% of ELG redshifts reliably within a redshift range of $0.6<z<1.6$. ELG targeting for DESI will be finalized during a `Survey Validation phase.
We characterise the selection cuts and clustering properties of a magnitude-limited sample of bright galaxies that is part of the Bright Galaxy Survey (BGS) of the Dark Energy Spectroscopic Instrument (DESI) using the ninth data release of the Legacy Imaging Surveys (DR9). We describe changes in the DR9 selection compared to the DR8 one as explored in Ruiz-Macias et al. (2021). We also compare the DR9 selection in three distinct regions: BASS/MzLS in the north Galactic Cap (NGC), DECaLS in the NGC, and DECaLS in the south Galactic Cap (SGC). We investigate the systematics associated with the selection and assess its completeness by matching the BGS targets with the Galaxy and Mass Assembly (GAMA) survey. We measure the angular clustering for the overall bright sample (r $leq$ 19.5) and as function of apparent magnitude and colour. This enables to determine the clustering strength and slope by fitting a power-law model that can be used to generate accurate mock catalogues for this tracer. We use a counts-in-cells technique to explore higher-order statistics and cross-correlations with external spectroscopic data sets in order to check the evolution of the clustering with redshift and the redshift distribution of the BGS targets using clustering-redshifts. While this work validates the properties of the BGS bright targets, the final target selection pipeline and clustering properties of the entire DESI BGS will be fully characterised and validated with the spectroscopic data of Survey Validation.
The DESI survey will measure large-scale structure using quasars as direct tracers of dark matter in the redshift range $0.9<z<2.1$ and using quasar Ly-$alpha$ forests at $z>2.1$. We present two methods to select candidate quasars for DESI based on imaging in three optical ($g, r, z$) and two infrared ($W1, W2$) bands. The first method uses traditional color cuts and the second utilizes a machine-learning algorithm.
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