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Full list of authors: Myers, Adam D.; Moustakas, John; Bailey, Stephen; Weaver, Benjamin A.; Cooper, Andrew P.; Forero-Romero, Jaime E.; Abolfathi, Bela; Alexander, David M.; Brooks, David; Chaussidon, Edmond; Chuang, Chia-Hsun; Dawson, Kyle; Dey, Arjun; Dey, Biprateep; Dhungana, Govinda; Doel, Peter; Fanning, Kevin; Gaztanaga, Enrique; Gontcho, Satya Gontcho; Gonzalez-Morales, Alma X.; Hahn, ChangHoon; Herrera-Alcantar, Hiram K.; Honscheid, Klaus; Ishak, Mustapha; Karim, Tanveer; Kirkby, David; Kisner, Theodore; Koposov, Sergey E.; Kremin, Anthony; Lan, Ting-Wen; Landriau, Martin; Lang, Dustin; Levi, Michael E.; Magneville, Christophe; Napolitano, Lucas; Martini, Paul; Meisner, Aaron; Newman, Jeffrey A.; Palanque-Delabrouille, Nathalie; Percival, Will; Poppett, Claire; Prada, Francisco; Raichoor, Anand; Ross, Ashley J.; Schlafly, Edward F.; Schlegel, David; Schubnell, Michael; Tan, Ting; Tarle, Gregory; Wilson, Michael J.; Yeche, Christophe; Zhou, Rongpu; Zhou, Zhimin; Zou, Hu.--This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited., In 2021 May, the Dark Energy Spectroscopic Instrument (DESI) began a 5 yr survey of approximately 50 million total extragalactic and Galactic targets. The primary DESI dark-time targets are emission line galaxies, luminous red galaxies, and quasars. In bright time, DESI will focus on two surveys known as the Bright Galaxy Survey and the Milky Way Survey. 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 code base. 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. © 2023. The Author(s). Published by the American Astronomical Society., A.D.M. and J.M. were supported by the U.S. Department of Energy, Office of Science, Office of High Energy Physics, under Award Numbers DE-SC0019022 and DE-SC0020086. A.P.C. is supported by a Taiwan Ministry of Education Yushan Fellowship and Taiwan Ministry of Science and Technology grant No. 109-2112-M-007-011-MY3. This research is supported by the Director, Office of Science, Office of High Energy Physics of the U.S. Department of Energy under Contract No. DEAC0205CH11231, 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 Technologies 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); the Ministry of Science and Innovation of Spain (MICINN), and by the DESI Member Institutions: https://www.desi.lbl.gov/collaborating-institutions., With funding from the Spanish government through the "Severo Ochoa Centre of Excellence" accreditation (CEX2021-001131-S).

Full list of authors: Chaussidon, Edmond; Yeche, Christophe; Palanque-Delabrouille, Nathalie; Alexander, David M.; Yang, Jinyi; Ahlen, Steven; Bailey, Stephen; Brooks, David; Cai, Zheng; Chabanier, Solene; Davis, Tamara M.; Dawson, Kyle; de laMacorra, Axel; Dey, Arjun; Dey, Biprateep; Eftekharzadeh, Sarah; Eisenstein, Daniel J.; Fanning, Kevin; Font-Ribera, Andreu; Gaztanaga, Enrique; Gontcho, Satya Gontcho A.; Gonzalez-Morales, Alma X.; Guy, Julien; Herrera-Alcantar, Hiram K.; Honscheid, Klaus; Ishak, Mustapha; Jiang, Linhua; Juneau, Stephanie; Kehoe, Robert; Kisner, Theodore; Kovacs, Andras; Kremin, Anthony; Lan, Ting-Wen; Landriau, Martin; Le Guillou, Laurent; Levi, Michael E.; Magneville, Christophe; Martini, Paul; Meisner, Aaron M.; Moustakas, John; Munoz-Gutierrez, Andrea; Myers, Adam D.; Newman, Jeffrey A.; Nie, Jundan; Percival, Will J.; Poppett, Claire; Prada, Francisco; Raichoor, Anand; Ravoux, Corentin; Ross, Ashley J.; Schlafly, Edward; Schlegel, David; Tan, Ting; Tarle, Gregory; Zhou, Rongpu; Zhou, Zhimin; Zou, Hu.--This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited., The Dark Energy Spectroscopic Instrument (DESI) survey will measure large-scale structures using quasars as direct tracers of dark matter in the redshift range 0.9 < z < 2.1 and using Lyα forests in quasar spectra at z > 2.1. We present several methods to select candidate quasars for DESI, using input photometric imaging in three optical bands (g, r, z) from the DESI Legacy Imaging Surveys and two infrared bands (W1, W2) from the Wide-field Infrared Survey Explorer. These methods were extensively tested during the Survey Validation of DESI. In this paper, we report on the results obtained with the different methods and present the selection we optimized for the DESI main survey. The final quasar target selection is based on a random forest algorithm and selects quasars in the magnitude range of 16.5 < r < 23. Visual selection of ultra-deep observations indicates that the main selection consists of 71% quasars, 16% galaxies, 6% stars, and 7% inconclusive spectra. Using the spectra based on this selection, we build an automated quasar catalog that achieves a fraction of true QSOs higher than 99% for a nominal effective exposure time of ∼1000 s. With a 310 deg−2 target density, the main selection allows DESI to select more than 200 deg−2 quasars (including 60 deg−2 quasars with z > 2.1), exceeding the project requirements by 20%. The redshift distribution of the selected quasars is in excellent agreement with quasar luminosity function predictions. © 2023. The Author(s). Published by the American Astronomical Society., A.D.M. was supported by the U.S. Department of Energy, Office of Science, Office of High Energy Physics, under award No. DE-SC0019022. T.W.L. was supported by the Ministry of Science and Technology (MOST 111-2112-M-002-015-MY3), the Ministry of Education, Taiwan (Yushan Young Scholar grant NTU-110VV007), National Taiwan University research grant (NTU-CC-111L894806), and NSF grant AST-1911140., With funding from the Spanish government through the "Severo Ochoa Centre of Excellence" accreditation (CEX2021-001131-S).

We present a measurement of baryonic acoustic oscillations (BAO) from Lyman-$\alpha$ (Ly$\alpha$) absorption and quasars at an effective redshift $z=2.33$ using the complete extended Baryonic Oscillation Spectroscopic Survey (eBOSS). The sixteenth and final eBOSS data release (SDSS DR16) contains all data from eBOSS and its predecessor, the Baryonic Oscillation Spectroscopic Survey (BOSS), providing $210,005$ quasars with $z_{q}>2.10$ that are used to measure Ly$\alpha$ absorption. We measure the BAO scale both in the auto-correlation of Ly$\alpha$ absorption and in its cross correlation with $341,468$ quasars with redshift $z_{q}>1.77$. Apart from the statistical gain from new quasars and deeper observations, the main improvements over previous work come from more accurate modeling of physical and instrumental correlations and the use of new sets of mock data. Combining the BAO measurement from the auto- and cross-correlation yields the constraints of the two ratios $D_{H}(z=2.33)/r_{d} = 8.99 \pm 0.19$ and $D_{M}(z=2.33)/r_{d} = 37.5 \pm 1.1$, where the error bars are statistical. These results are within $1.5\sigma$ of the prediction of the flat-$\Lambda$CDM cosmology of Planck~(2016). The analysis code, \texttt{picca}, the catalog of the flux-transmission field measurements, and the $\Delta \chi^{2}$ surfaces are publicly available., Comment: 37 pages, 23 figures, Matches the published version by ApJ