Abstract
We describe the Milky Way Survey (MWS) that will be undertaken with the Dark Energy Spectroscopic Instrument (DESI) on the Mayall 4 m telescope at the Kitt Peak National Observatory. Over the next 5 yr DESI MWS will observe approximately seven million stars at Galactic latitudes ∣b∣ > 20°, with an inclusive target selection scheme focused on the thick disk and stellar halo. MWS will also include several high-completeness samples of rare stellar types, including white dwarfs, low-mass stars within 100 pc of the Sun, and horizontal branch stars. We summarize the potential of DESI to advance understanding of the Galactic structure and stellar evolution. We introduce the final definitions of the main MWS target classes and estimate the number of stars in each class that will be observed. We describe our pipelines for deriving radial velocities, atmospheric parameters, and chemical abundances. We use ≃500,000 spectra of unique stellar targets from the DESI Survey Validation program (SV) to demonstrate that our pipelines can measure radial velocities to ≃1 km s−1 and [Fe/H] accurate to ≃0.2 dex for typical stars in our main sample. We find the stellar parameter distributions from ≈100 deg2 of SV observations with ≳90% completeness on our main sample are in good agreement with expectations from mock catalogs and previous surveys.
Original language | English |
---|---|
Article number | 37 |
Number of pages | 32 |
Journal | Astrophysical Journal |
Volume | 947 |
Issue number | 1 |
DOIs | |
Publication status | Published - 18 Apr 2023 |
Keywords
- UKRI
- STFC
- ST/T000406/1
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In: Astrophysical Journal, Vol. 947, No. 1, 37, 18.04.2023.
Research output: Contribution to journal › Article › peer-review
TY - JOUR
T1 - Overview of the DESI Milky Way Survey
AU - DESI Collaboration
AU - Cooper, Andrew P.
AU - Koposov, Sergey E.
AU - Allende Prieto, Carlos
AU - Manser, Christopher J.
AU - Kizhuprakkat, Namitha
AU - Myers, Adam D.
AU - Dey, Arjun
AU - Gänsicke, Boris T.
AU - Li, Ting S.
AU - Rockosi, Constance
AU - Valluri, Monica
AU - Najita, Joan
AU - Deason, Alis
AU - Raichoor, Anand
AU - Wang, M. Y.
AU - Ting, Y. S.
AU - Kim, Bokyoung
AU - Carrillo, Andreia
AU - Wang, Wenting
AU - Beraldo e Silva, Leandro
AU - Han, Jiwon Jesse
AU - Ding, Jiani
AU - Sánchez-Conde, Miguel
AU - Aguilar, Jessica N.
AU - Ahlen, Steven
AU - Bailey, Stephen
AU - Belokurov, Vasily
AU - Brooks, David
AU - Cunha, Katia
AU - Dawson, Kyle
AU - de la Macorra, Axel
AU - Doel, Peter
AU - Eisenstein, Daniel J.
AU - Fagrelius, Parker
AU - Fanning, Kevin
AU - Font-Ribera, Andreu
AU - Forero-Romero, Jaime E.
AU - Gaztañaga, Enrique
AU - A Gontcho, Satya Gontcho
AU - Guy, Julien
AU - Honscheid, Klaus
AU - Kehoe, Robert
AU - Kisner, Theodore
AU - Kremin, Anthony
AU - Landriau, Martin
AU - Levi, Michael E.
AU - Martini, Paul
AU - Meisner, Aaron M.
AU - Miquel, Ramon
AU - Percival, Will J.
N1 - Funding Information: This research is supported by the Director, Office of Science, Office of High Energy Physics of the U.S. Department of Energy (DOE), under contract No. DE-AC02-05CH11231, and by the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility under the same contract. Additional support for DESI is provided by the U.S. National Science Foundation, Division of Astronomical Sciences, under contract No. AST-0950945 to the NSF's National Optical-infrared Astronomy Research Laboratory; the Science and Technology Facilities Council of the United Kingdom; the Gordon and Betty Moore Foundation; the Heising-Simons Foundation; the French Alternative Energies and Atomic Energy Commission (CEA); the National Council of Science and Technology of Mexico (CONACYT); MICINN; and the DESI member institutions: https://www.desi.lbl.gov/collaborating-institutions . Funding Information: The DESI Legacy Imaging Surveys consist of three individual and complementary projects: the Dark Energy Camera Legacy Survey (DECaLS), the Beijing–Arizona Sky Survey (BASS), and the Mayall z-band Legacy Survey (MzLS). DECaLS, BASS, and MzLS include data obtained, respectively, at the Blanco telescope, Cerro Tololo Inter-American Observatory, NSF's NOIRLab; at the Bok telescope, Steward Observatory, University of Arizona; and at the Mayall telescope, Kitt Peak National Observatory, NOIRLab. NOIRLab is operated by the Association of Universities for Research in Astronomy (AURA) under a cooperative agreement with the National Science Foundation. Pipeline processing and analyses of the data were supported by NOIRLab and the Lawrence Berkeley National Laboratory (LBNL). The Legacy Surveys also use data products from the Near-Earth Object Wide-field Infrared Survey Explorer (NEOWISE), a project of the Jet Propulsion Laboratory/California Institute of Technology, funded by the National Aeronautics and Space Administration. The Legacy Surveys were supported by the Director, Office of Science, Office of High Energy Physics of the U.S. DOE; the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility; the U.S. National Science Foundation, Division of Astronomical Sciences; the National Astronomical Observatories of China, Chinese Academy of Sciences; and the Chinese National Natural Science Foundation. LBNL is managed by the regents of the University of California under contract to the U.S. DOE. The complete acknowledgments can be found at https://www.legacysurvey.org/ . Funding Information: Funding for SDSS-IV has been provided by the Alfred P. Sloan Foundation, the U.S. DOE Office of Science, and the participating institutions. SDSS-IV acknowledges support and resources from the Center for High Performance Computing at the University of Utah. The SDSS website is www.sdss.org . Funding Information: We thank the reviewer, Matthias Steinmetz, for his thorough reading of our manuscript and constructive suggestions. A.P.C. and N.K. are supported by a Taiwan Ministry of Education (MoE) Yushan Fellowship awarded to A.P.C., and by Taiwan National Science and Technology Council (NSTC) grant 109-2112-M-007-011-MY3. This work used high-performance computing facilities operated by the Center for Informatics and Computation in Astronomy (CICA) at National Tsing Hua University. This equipment was funded by MoE, NSTC, and National Tsing Hua University. C.A.P. acknowledges financial support from the Spanish Ministry of Science and Innovation (MICINN) projects AYA2017-86389-P and PID2020-117493GB-I00. C.J.M. acknowledges financial support from Imperial College London through an Imperial College Research Fellowship grant. M.V. and L.B.e.S. acknowledge support from NASA-ATP award 80NSSC20K0509. The work of A.D. and J.N. is supported by NOIRLab, which is managed by the Association of Universities for Research in Astronomy (AURA) under a cooperative agreement with the National Science Foundation. T.S.L. acknowledges financial support from the Natural Sciences and Engineering Research Council of Canada (NSERC) through grant RGPIN-2022-04794. B.T.G. was supported by grant ST/T000406/1 from the Science and Technology Facilities Council (STFC). This project has received funding from the European Research Council under the European Union's Horizon 2020 research and innovation program (grant agreement No. 101020057). This research made use of computing time available on the high-performance computing system at the Instituto de Astrofisica de Canarias. The authors thankfully acknowledge the technical expertize and assistrovided by the Spanish Supercomputing Network (Red Espanola de Supercomputacion), as well as the computing resources provided by the LaPalma Supercomputer and the Diva cluster, both located at the Instituto de Astrofisica de Canarias. Funding Information: This work has made use of data from the European Space Agency (ESA) mission Gaia ( https://www.cosmos.esa.int/gaia ), processed by the Gaia Data Processing and Analysis Consortium (DPAC, https://www.cosmos.esa.int/web/gaia/dpac/consortium ). Funding for the DPAC has been provided by national institutions, in particular the institutions participating in the Gaia Multilateral Agreement. Funding Information: We thank the reviewer, Matthias Steinmetz, for his thorough reading of our manuscript and constructive suggestions. A.P.C. and N.K. are supported by a Taiwan Ministry of Education (MoE) Yushan Fellowship awarded to A.P.C., and by Taiwan National Science and Technology Council (NSTC) grant 109-2112-M-007-011-MY3. This work used high-performance computing facilities operated by the Center for Informatics and Computation in Astronomy (CICA) at National Tsing Hua University. This equipment was funded by MoE, NSTC, and National Tsing Hua University. C.A.P. acknowledges financial support from the Spanish Ministry of Science and Innovation (MICINN) projects AYA2017-86389-P and PID2020-117493GB-I00. C.J.M. acknowledges financial support from Imperial College London through an Imperial College Research Fellowship grant. M.V. and L.B.e.S. acknowledge support from NASA-ATP award 80NSSC20K0509. The work of A.D. and J.N. is supported by NOIRLab, which is managed by the Association of Universities for Research in Astronomy (AURA) under a cooperative agreement with the National Science Foundation. T.S.L. acknowledges financial support from the Natural Sciences and Engineering Research Council of Canada (NSERC) through grant RGPIN-2022-04794. B.T.G. was supported by grant ST/T000406/1 from the Science and Technology Facilities Council (STFC). This project has received funding from the European Research Council under the European Union's Horizon 2020 research and innovation program (grant agreement No. 101020057). This research made use of computing time available on the high-performance computing system at the Instituto de Astrofisica de Canarias. The authors thankfully acknowledge the technical expertize and assistrovided by the Spanish Supercomputing Network (Red Espanola de Supercomputacion), as well as the computing resources provided by the LaPalma Supercomputer and the Diva cluster, both located at the Instituto de Astrofisica de Canarias. Publisher Copyright: © 2023. The Author(s). Published by the American Astronomical Society.
PY - 2023/4/18
Y1 - 2023/4/18
N2 - We describe the Milky Way Survey (MWS) that will be undertaken with the Dark Energy Spectroscopic Instrument (DESI) on the Mayall 4 m telescope at the Kitt Peak National Observatory. Over the next 5 yr DESI MWS will observe approximately seven million stars at Galactic latitudes ∣b∣ > 20°, with an inclusive target selection scheme focused on the thick disk and stellar halo. MWS will also include several high-completeness samples of rare stellar types, including white dwarfs, low-mass stars within 100 pc of the Sun, and horizontal branch stars. We summarize the potential of DESI to advance understanding of the Galactic structure and stellar evolution. We introduce the final definitions of the main MWS target classes and estimate the number of stars in each class that will be observed. We describe our pipelines for deriving radial velocities, atmospheric parameters, and chemical abundances. We use ≃500,000 spectra of unique stellar targets from the DESI Survey Validation program (SV) to demonstrate that our pipelines can measure radial velocities to ≃1 km s−1 and [Fe/H] accurate to ≃0.2 dex for typical stars in our main sample. We find the stellar parameter distributions from ≈100 deg2 of SV observations with ≳90% completeness on our main sample are in good agreement with expectations from mock catalogs and previous surveys.
AB - We describe the Milky Way Survey (MWS) that will be undertaken with the Dark Energy Spectroscopic Instrument (DESI) on the Mayall 4 m telescope at the Kitt Peak National Observatory. Over the next 5 yr DESI MWS will observe approximately seven million stars at Galactic latitudes ∣b∣ > 20°, with an inclusive target selection scheme focused on the thick disk and stellar halo. MWS will also include several high-completeness samples of rare stellar types, including white dwarfs, low-mass stars within 100 pc of the Sun, and horizontal branch stars. We summarize the potential of DESI to advance understanding of the Galactic structure and stellar evolution. We introduce the final definitions of the main MWS target classes and estimate the number of stars in each class that will be observed. We describe our pipelines for deriving radial velocities, atmospheric parameters, and chemical abundances. We use ≃500,000 spectra of unique stellar targets from the DESI Survey Validation program (SV) to demonstrate that our pipelines can measure radial velocities to ≃1 km s−1 and [Fe/H] accurate to ≃0.2 dex for typical stars in our main sample. We find the stellar parameter distributions from ≈100 deg2 of SV observations with ≳90% completeness on our main sample are in good agreement with expectations from mock catalogs and previous surveys.
KW - UKRI
KW - STFC
KW - ST/T000406/1
UR - http://www.scopus.com/inward/record.url?scp=85153533198&partnerID=8YFLogxK
U2 - 10.3847/1538-4357/acb3c0
DO - 10.3847/1538-4357/acb3c0
M3 - Article
AN - SCOPUS:85153533198
SN - 0004-637X
VL - 947
JO - Astrophysical Journal
JF - Astrophysical Journal
IS - 1
M1 - 37
ER -