Overview of the DESI Milky Way Survey

Cooper, Andrew P.; Koposov, Sergey E.; Prieto, Carlos Allende; Manser, Christopher J.; Kizhuprakkat, Namitha; Myers, Adam D.; Dey, Arjun; Gaensicke, Boris T.; Li, Ting S.; Rockosi, Constance; Valluri, Monica; Najita, Joan; Deason, Alis; Raichoor, Anand; Wang, Mei-Yu; Ting, Yuan-Sen; Kim, Bokyoung; Carrillo, Andreia; Wang, Wenting; Silva, Leandro Beraldo e; Han, Jiwon Jesse; Ding, Jiani; Sanchez-Conde, Miguel; Aguilar, Jessica N.; Ahlen, Steven; Bailey, Stephen; Belokurov, Vasily; Brooks, David; Cunha, Katia; Dawson, Kyle; de la Macorra, Axel; Doel, Peter; Eisenstein, Daniel J.; Fagrelius, Parker; Fanning, Kevin; Font-Ribera, Andreu; Forero-Romero, Jaime E.; Gaztanaga, Enrique; Gontcho, Satya Gontcho A; Guy, Julien; Honscheid, Klaus; Kehoe, Robert; Kisner, Theodore; Kremin, Anthony; Landriau, Martin; Levi, Michael E.; Martini, Paul; Meisner, Aaron M.; Miquel, Ramon; Moustakas, John; Nie, Jundan; Palanque-Delabrouille, Nathalie; Percival, Will J.; Poppett, Claire; Prada, Francisco; Rehemtulla, Nabeel; Schlafly, Edward; Schlegel, David; Schubnell, Michael; Sharples, Ray M.; Tarle, Gregory; Wechsler, Risa H.; Weinberg, David H.; Zhou, Zhimin; Zou, Hu

doi:10.48550/arxiv.2208.08514

Cited by 21 publications

(37 citation statements)

References 231 publications

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“…In this paper, we have provided a detailed overview of the DESI target selection pipeline. The exact algorithms used to classify specific subsets of DESI bright-time and dark-time targets are detailed in other papers (Raichoor et al 2022;Zhou et al 2022;Chaussidon et al 2022a;Cooper et al 2022;Hahn et al 2022) but aspects of how these targeting algorithms are implemented are crucial to understanding how to work with DESI data. This paper also details the approaches used to classify targets to help calibrate DESI spectroscopy, such as GFA targets and blank sky locations.…”

Section: Discussionmentioning

confidence: 99%

“…The primary dark-time target classes observed by DESI (DESI Collaboration et al 2016b) are ELGs (Raichoor et al 2020(Raichoor et al , 2022, LRGs (Zhou et al 2020(Zhou et al , 2022 and QSOs (quasi-stellar objects, also known as quasars; Yèche et al 2020;Chaussidon et al 2022a). During survey bright-time, DESI also targets galaxies as part of a dedicated Bright Galaxy Survey (BGS; Ruiz-Macias et al 2020;Hahn et al 2022), and a variety of Galactic sources as part of a Milky Way Survey (MWS; Allende Cooper et al 2022). Finally, to calibrate the output from its spectroscopic pipeline, DESI also targets calibration sources such as standard stars and blank sky locations.…”

Section: An Overview Of Desi Target Classesmentioning

confidence: 99%

“…The Gaia standard star selections are designed to approximate the principal standard star classes but using imaging from Gaia in place of Legacy Surveys quantities. The STD WD and GAIA STD WD classes are identical to each other -and to the MWS WD class described in Cooper et al (2022) -so won't be further detailed here.…”

Section: Standard Starsmentioning

confidence: 99%

“…Target selection approaches for DESI are, themselves, varied and extensive. Other publications that accompany this work include a paper describing the DESI Survey Validation (SV) phase (DESI collaboration et al 2023a), two papers describing how visual inspection of spectra of targets acquired during SV produced truth tables to inform target selection for the DESI Main Survey (Alexander et al 2022;Lan et al 2022), and a series of five papers detailing the selection of DESI bright-time and dark-time science targets (Chaussidon et al 2022a;Zhou et al 2022;Raichoor et al 2022;Cooper et al 2022;Hahn et al 2022, see also §4.1.1).…”

Section: Introductionmentioning

confidence: 99%

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The Target-selection Pipeline for the Dark Energy Spectroscopic Instrument

Myers,

Moustakas,

Bailey

et al. 2022

Preprint

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In May, 2021, the Dark Energy Spectroscopic Instrument (DESI) began a five-year survey of approximately 50 million total extragalactic and Galactic targets. The primary DESI dark-time targets are Emission Line Galaxies (ELGs), Luminous Red Galaxies (LRGs) and quasars (QSOs). In bright time, DESI will focus on two surveys known as the Bright Galaxy Survey (BGS) and the Milky Way Survey (MWS). DESI also observes a selection of "secondary" targets for bespoke science goals. This paper gives an overview of the publicly available pipeline (desitarget) used to process targets for DESI observations. Highlights include details of the different DESI survey targeting phases, the targeting ID (TARGETID) used to define unique targets, the bitmasks used to indicate a particular type of target, the data model and structure of DESI targeting files, and examples of how to access and use the desitarget codebase. This paper will also describe "supporting" DESI target classes, such as standard stars, sky locations, and random catalogs that mimic the angular selection function of DESI targets. The DESI target selection pipeline is complex and sizable -this paper attempts to summarize the most salient information required to understand and work with DESI targeting data.

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Section: Discussionmentioning

confidence: 99%

Section: An Overview Of Desi Target Classesmentioning

confidence: 99%

Section: Standard Starsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The Target-selection Pipeline for the Dark Energy Spectroscopic Instrument

Myers,

Moustakas,

Bailey

et al. 2022

Preprint

Self Cite

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“…• Bright galaxies (bright galaxy survey, BGS) (Hahn et al 2022), a galaxy sample whose redshifts can be obtained during the bright time of the observations together with the Milky Way stars (Cooper et al 2022). The BGS consists of two selections, (1) BGS bright -a magnitude limit sample with r < 19.5, which is similar to the depth of the Galaxy And Mass Assembly (GAMA) survey (Driver et al 2011) and about 2 magnitude deeper than the main galaxy sample from the Sloan Digital Sky Survey (Strauss et al 2002), and (2) BGS faint -a sample of fainter 19.5 < r < 20.175 galaxies with a color-selection to achieve high redshift efficiency.…”

Section: Introductionmentioning

confidence: 99%

The DESI Survey Validation: Results from Visual Inspection of Bright Galaxies, Luminous Red Galaxies, and Emission Line Galaxies

Lan,

Tojeiro,

Armengaud

et al. 2022

Preprint

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The Dark Energy Spectroscopic Instrument (DESI) Survey has obtained a set of spectroscopic measurements of galaxies for validating the final survey design and target selections. To assist these tasks, we visually inspect (VI) DESI spectra of approximately 2,500 bright galaxies, 3,500 luminous red galaxies, and 10,000 emission line galaxies, to obtain robust redshift identifications. We then utilize the VI redshift information to characterize the performance of the DESI operation. Based on the VI catalogs, our results show that the final survey design yields samples of bright galaxies, luminous red galaxies, and emission line galaxies with purity greater than 99%. Moreover, we demonstrate that the precision of the redshift measurements is approximately 10 km/s for bright galaxies and emission line galaxies and approximately 40 km/s for luminous red galaxies. The average redshift accuracy is within 10 km/s for the three types of galaxies. The VI process also helps to improve the quality of the DESI data by identifying spurious spectral features introduced by the pipeline. Finally, we show examples of unexpected real astronomical objects, such as Lyman α emitters and strong lensing candidates, identified by VI. These results demonstrate the importance and utility of visually inspecting data from incoming and upcoming surveys, especially during their early operation phases.

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Unravelling the mass spectrum of destroyed dwarf galaxies with the metallicity distribution function

Deason

Koposov

Fattahi

et al. 2023

Monthly Notices of the Royal Astronomical Society

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Accreted stellar populations are comprised of the remnants of destroyed galaxies, and often dominate the ‘stellar haloes’ of galaxies such as the Milky Way (MW). This ensemble of external contributors is a key indicator of the past assembly history of a galaxy. We introduce a novel statistical method that uses the unbinned metallicity distribution function (MDF) of a stellar population to estimate the mass spectrum of its progenitors. Our model makes use of the well-known mass-metallicity relation of galaxies and assumes Gaussian MDF distributions for individual progenitors: the overall MDF is thus a mixture of MDFs from smaller galaxies. We apply the method to the stellar halo of the MW, as well as the classical MW satellite galaxies. The stellar components of the satellite galaxies have relatively small sample sizes, but we do not find any evidence for accreted populations with L > Lhost/100. We find that the MW stellar halo has N ∼ 1 − 3 massive progenitors (L ≳ 108L⊙) within 10 kpc, and likely several hundred progenitors in total. We also test our method on simulations of MW-mass haloes, and find that our method is able to recover the true accreted population within a factor of two. Future datasets will provide MDFs with orders of magnitude more stars, and this method could be a powerful technique to quantify the accreted populations down to the ultra-faint dwarf mass-scale for both the MW and its satellites.

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Overview of the DESI Milky Way Survey

Cited by 21 publications

References 231 publications

The Target-selection Pipeline for the Dark Energy Spectroscopic Instrument

The Target-selection Pipeline for the Dark Energy Spectroscopic Instrument

The DESI Survey Validation: Results from Visual Inspection of Bright Galaxies, Luminous Red Galaxies, and Emission Line Galaxies

Unravelling the mass spectrum of destroyed dwarf galaxies with the metallicity distribution function

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