The eighteenth data release DR18 of the Sloan Digital Sky Survey SDSS is the first one for SDSSV the fifth generation of the survey. SDSSV comprises three primary scientific programs or Mappers the Milky Way Mapper MWM the Black Hole Mapper BHM and the Local Volume Mapper. This data release contains extensive targeting information for the two multiobject spectroscopy programs MWM and BHM including input catalogs and selection functions for their numerous scientific objectives. We describe the production of the targeting databases and their calibration and scientifically focused components. DR18 also includes 25000 new SDSS spectra and supplemental information for Xray sources identified by eROSITA in its eFEDS field. We present updates to some of the SDSS software pipelines and preview changes anticipated for DR19. We also describe three valueadded catalogs VACs based on SDSSIV data that have been published since DR17 and one VAC based on the SDSSV data in the eFEDS field.
['Surveys', 'Astronomy databases', 'Astronomy data acquisition', 'Astronomy software', '1671', '83', '1860', '1855', 'Astrophysics - Astrophysics of Galaxies', 'Astrophysics - Cosmology and Nongalactic Astrophysics', 'Astrophysics - High Energy Astrophysical Phenomena']
The Eighteenth Data Release of the Sloan Digital Sky Surveys Targeting and First Spectra from SDSSV
{'The Eighteenth Data Release of the Sloan Digital Sky Surveys: Targeting and First Spectra from SDSS-V': "Andr'es Almeida, 1 Scott F. Anderson, 2 Maria Argudo-Fern'andez, 3, 4, 5 Carles Badenes, 6 Kat Barger, 7 Jorge K. Barrera-Ballesteros, 8 Chad F. Bender, 9 Erika Benitez, 8 Felipe Besser, 10 Jonathan C. Bird , 11 Dmitry Bizyaev, 12, 13 Michael R. Blanton, 14 John Bochanski, 15 Jo Bovy, 16, 17 William Nielsen Brandt, 18, 19, 20 Joel R. Brownstein , 21 Johannes Buchner, 22 Esra Bulbul, 22 Joseph N. Burchett, 13 Mariana Cano D'ıaz, 8 Joleen K. Carlberg , 23 Andrew R. Casey, 24, 25 Vedant Chandra , 26 Brian Cherinka, 23 Cristina Chiappini, 27 Abigail A. Coker , 21 Johan Comparat, 22 Charlie Conroy, 26 Gabriella Contardo, 28 Arlin Cortes, 10 Kevin Covey, 29 Jeffrey D. Crane, 30 Katia Cunha, 9 Collin Dabbieri, 11 James W. Davidson Jr., 1 Megan C. Davis, 31 Nathan De Lee , 32 Jos'e Eduardo M'endez Delgado, 33 Sebastian Demasi, 2 Francesco Di Mille, 10 John Donor, 7 Peter Dow, 1 Tom Dwelly, 22 Mike Eracleous , 18, 19 Jamey Eriksen, 12, 13 Xiaohui Fan, 9 Emily Farr, 34 Sara Frederick , 11 Logan Fries , 31 Peter Frinchaboy, 7 Boris T. Gansicke , 35 Junqiang Ge, 36 Consuelo Gonz'alez ' Avila, 10 Katie Grabowski, 12, 13 Catherine Grier, 37 Guillaume Guiglion, 38 Pramod Gupta, 2 Patrick Hall, 39 Keith Hawkins, 40 Christian R. Hayes , 41 J. J. Hermes, 42 Lorena Hern'andez-Garc'ıa, 43, 44 David W. Hogg, 14 Jon A. Holtzman , 13 Hector Javier Ibarra-Medel, 45, 46 Alexander Ji, 47, 48 Paula Jofre, 49, 50 Jennifer A. Johnson, 51, 52 Amy M. Jones, 23 Karen Kinemuchi, 12, 13 Matthias Kluge, 22 Anton Koekemoer, 23 Juna A. Kollmeier, 30, 53 Marina Kounkel, 11 Dhanesh Krishnarao, 54 Mirko Krumpe, 27 Ivan Lacerna, 46, 43 Paulo Jakson Assuncao Lago, 10 Chervin Laporte, 55 Chao Liu, 36 Ang Liu, 22 Xin Liu, 45, 56 Alexandre Roman Lopes, 57 Matin Macktoobian , 58 Steven R. Majewski, 1 Viktor Malanushenko, 12, 13 Dan Maoz, 59 Thomas Masseron, 60, 61 Karen L. Masters, 62 Gal Matijevic, 27 Aidan McBride , 21 Ilija Medan, 63 Andrea Merloni, 22 Sean Morrison, 45 Natalie Myers, 7 Szabolcs M'esz'aros, 64, 65 C. Alenka Negrete, 8 David L. Nidever, 66 Christian Nitschelm , 67 Daniel Oravetz, 12, 13 Audrey Oravetz, 12, 13 Kaike Pan, 12, 13 Yingjie Peng, 68, 69 Marc H. Pinsonneault, 51 Rick Pogge , 70 Dan Qiu, 36 Anna Barbara de Andrade Queiroz, 27 Solange V. Ramirez, 30 Hans-Walter Rix, 38 Daniela Fern'andez Rosso, 10 Jessie Runnoe, 11 Mara Salvato, 22 Sebastian F. Sanchez, 8 Felipe A. Santana, 71 Andrew Saydjari , 26 Conor Sayres, 2 Kevin C. Schlaufman , 72 Donald P. Schneider, 18, 19 Axel Schwope, 27 Javier Serna, 73 Yue Shen, 45 Jennifer Sobeck , 74 Ying-Yi Song, 16, 17 Diogo Souto, 75 Taylor Spoo, 7 Keivan G. Stassun , 11 Matthias Steinmetz, 27 Ilya Straumit, 51, 76, 59 Guy Stringfellow, 77 Jos'e S'anchez-Gallego, 2 Manuchehr Taghizadeh-Popp, 72 Jamie Tayar, 78 Ani Thakar, 72 Patricia B. Tissera, 79 Andrew Tkachenko, 76 Hector Hernandez Toledo, 8 Benny Trakhtenbrot , 59 Jos'e G. Fern'andez-Trincado, 80 Nicholas Troup, 81 Jonathan R. Trump, 31 Sarah Tuttle, 2 Natalie Ulloa, 10 Jose Antonio Vazquez-Mata, 8, 82 Pablo Vera Alfaro, 10 Sandro Villanova, 83 Stefanie Wachter, 30 Anne-Marie Weijmans, 84 Adam Wheeler, 51 John Wilson, 1 Leigh Wojno, 38 Julien Wolf, 22, 85 Xiang-Xiang Xue, 36 Jason E. Ybarra, 86, 87 Eleonora Zari, 38 and  \n21  \nGail Zasowski  \n1 Department of Astronomy, University of Virginia, Charlottesville, VA 22904-4325, USA 2 Department of Astronomy, University of Washington, Box 351580, Seattle, WA 98195, USA 3 Instituto de F'ısica, Pontificia Universidad Cat'olica de Valpara'ıso, Valpara'ıso, Chile 4 Universidad de Granada (UGR), Departamento de F'ısica Te'orica y del Cosmos, 18071, Granada, Spain 5 Instituto Universitario Carlos I de F'ısica Te'orica y Computacional, Universidad de Granada, 18071, Granada, Spain 6 PITT PACC, Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh, PA 15260, USA 7 Department of Physics & Astronomy, Texas Christian University, Fort Worth, TX 76129, USA 8 Instituto de Astronom'ıa, Universidad Nacional Aut'onoma de M'exico, A.P. 70-264, 04510, Mexico, D.F., M'exico 9 Steward Observatory, University of Arizona, 933 North Cherry Avenue, Tucson, AZ 85721-0065, USA 10 Las Campanas Observatory, Ra'ul Bitr'an 1200, La Serena, Chile 11 Department of Physics and Astronomy, Vanderbilt University, VU Station 1807, Nashville, TN 37235, USA 12 Apache Point Observatory, P.O. Box 59, Sunspot, NM 88349 13  \nDepartment of Astronomy, New Mexico State University, Las Cruces, NM 88003, USA  \ngail.zasowski@gmail.com  \n- 14 Center for Cosmology and Particle Physics, Department of Physics, 726 Broadway, Room 1005, New York University, New York, NY 10003, USA  \n15  \nRider University, 2083 Lawrenceville Road, Lawrenceville, NJ 08648, USA  \n- 16 David A. Dunlap Department of Astronomy & Astrophysics, University of Toronto, 50 St. George Street, Toronto, Ontario M5S 3H4, Canada  \n17  \nDunlap Institute for Astronomy & Astrophysics, University of Toronto, 50 St. George Street, Toronto, Ontario M5S 3H4, Canada  \n18  \nDepartment of Astronomy & Astrophysics, The Pennsylvania State University, University Park, PA 16802, USA  \n19  \n21  \n24  \nInstitute for Gravitation and the Cosmos, The Pennsylvania State University, University Park, PA 16802, USA  \n20  \nDepartment of Physics, The Pennsylvania State University, University Park, PA 16802, USA  \nDepartment of Physics and Astronomy, University of Utah, 115 S. 1400 E., Salt Lake City, UT 84112, USA  \n22  \nMax-Planck-Institut fur extraterrestrische Physik, Giessenbachstraße 1, 85748 Garching, Germany  \n23  \nSpace Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218, USA  \nSchool of Physics & Astronomy, Monash University, Wellington Road, Clayton, Victoria 3800, Australia  \n25  \nCenter of Excellence for Astrophysics in Three Dimensions (ASTRO-3D), Australia  \nCenter for Astrophysics  \n|  \nHarvard & Smithsonian, 60 Garden St, Cambridge, MA 02138, USA  \n26  \n- 27 Leibniz-Institut fur Astrophysik Potsdam (AIP), An der Sternwarte 16, D-14482 Potsdam, Germany 28 SISSA, Scuola Internazionale Superiore di Studi Avanzati\n- 29 Department of Physics and Astronomy, Western Washington University, 516 High Street, Bellingham, WA 98225, USA 30 The Observatories of the Carnegie Institution for Science, 813 Santa Barbara Street, Pasadena, CA 91101, USA 31 Department of Physics, University of Connecticut, 2152 Hillside Road, Unit 3046, Storrs, CT 06269, USA\n- 32 Department of Physics, Geology, and Engineering Technology, Northern Kentucky University, Highland Heights, KY 41099 33 Astronomisches Rechen-Institut, Zentrum fur Astronomie der Universitat Heidelberg, Monchhofstr. 12-14, D-69120 Heidelberg, Germany\n- 34 Laboratory for Atmospheric and Space Physics, University of Colorado, 1234 Innovation Drive, Boulder, CO 80303, USA 35 Department of Physics, University of Warwick, Coventry CV4 7AL, UK\n- 36 National Astronomical Observatories, Chinese Academy of Sciences, 20A Datun Road, Chaoyang, Beijing 100101, China 37 Department of Astronomy, University of Wisconsin-Madison, 475N. Charter St., Madison WI 53703, USA 38 Max-Planck-Institut fur Astronomie, Konigstuhl 17, D-69117 Heidelberg, Germany  \n39  \nDepartment of Physics and Astronomy, York University, 4700 Keele St., Toronto, Ontario M3J 1P3, Canada  \n40  \nDepartment of Astronomy, University of Texas at Austin, Austin, TX 78712, USA  \nNRC Herzberg Astronomy and Astrophysics Research Centre, 5071 West Saanich Road, Victoria, B.C., Canada, V9E 2E7  \n42  \nAstronomy Department, Boston University, 725 Commonwealth Ave, Boston, MA 02215, USA  \nMillennium Institute of Astrophysics (MAS), Nuncio Monse˜nor S'otero Sanz 100, Providencia, Santiago, Chile  \n43  \nInstituto de F'ısica y Astronom'ıa, Universidad de Valpara'ıso, Av. Gran Breta˜na 1111, Playa Ancha, Casilla 5030, Chile  \n45  \nDepartment of Astronomy, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA  \nInstituto de Astronom'ıa y Ciencias Planetarias, Universidad de Atacama, Copayapu 485, Copiap'o, Chile  \n47  \nDepartment of Astronomy and Astrophysics, University of Chicago, Chicago, IL 60637, USA  \n48  \nKavli Institute for Cosmological Physics, University of Chicago, Chicago, IL 60637, USA  \n- 49 N'ucleo de Astronom'ıa de la Facultad de Ingenier'ıa y Ciencias, Universidad Diego Portales, Av. Ej'ercito Libertador 441, Santiago, Chile  \n50 Millenium Nucleus ERIS  \n51 Department of Astronomy, The Ohio State University, 140 W. 18th Ave., Columbus, OH 43210, USA 52 Center for Cosmology and AstroParticle Physics, Ohio State University, 191 West Woodruff Ave, Columbus, OH, 43210, USA 53 Canadian Institute for Theoretical Astrophysics, University of Toronto, Toronto, ON M5S-98H, Canada 54 Department of Physics, Colorado College, 14 East Cache la Poudre St., Colorado Springs, CO, 80903, USA 55 Institut de Ci'encies del Cosmos, Universitat de Barcelona, Mart'ı Franqu'es 1, 08028 Barcelona, Spain 56 National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA 57 Departamento de F'ısica, Facultad de Ciencias, Universidad de La Serena, Cisternas 1200, La Serena, Chile 58 Electrical and Computer Engineering Department, University of Alberta, Edmonton, AB, Canada 59 School of Physics and Astronomy, Tel Aviv University, Tel Aviv 69978, Israel 60 nstituto de Astrof'ısica de Canarias, 38205 La Laguna, Tenerife, Spain 61 Departamento de Astrof'ısica, Universidad de La Laguna, 38206 La Laguna, Tenerife, Spain 62 Departments of Physics and Astronomy, Haverford College, 370 Lancaster Avenue, Haverford, PA 19041, USA 63 Department of Physics and Astronomy, Georgia State University, Atlanta, GA 30302, USA 64 ELTE Gothard Astrophysical Observatory, H-9704 Szombathely, Szent Imre herceg st. 112, Hungary 65 MTA-ELTE Lendulet 'Momentum' Milky Way Research Group, Hungary 66 Department of Physics, Montana State University, P.O. Box 173840, Bozeman, MT 59717, USA  \n41  \n44  \n46  \n- 67 Centro de Astronom'ıa (CITEVA), Universidad de Antofagasta, Avenida Angamos 601, Antofagasta 1270300, Chile 68 Department of Astronomy, School of Physics, Peking University, Beijing 100871, China  \n69 Kavli Institute for Astronomy and Astrophysics, Peking University, Beijing 100871, China  \n70 Department of Astronomy and Center for Cosmology and AstroParticle Physics, The Ohio State University, 140 W. 18th Ave, Columbus, OH, 43210, USA  \n- 71 Departamento de Astronom'ıa, Universidad de Chile, Av. Libertador Bernardo O'Higgins 1058, Santiago de Chile  \n72 William H. Miller III Department of Physics and Astronomy, Johns Hopkins University, 3400 N Charles Street, Baltimore, MD 21218, USA  \n73 Instituto de Astronom'ıa, Universidad Nacional Aut'onoma de M'exico, Ensenada, Baja California, M'exico  \n74 Maunakea Spectroscopic Explorer, CFHT, 65-1238 Mamalahoa Hwy, Kamuela, Hawaii 96743  \n- 75 Departamento de F'ısica, Universidade Federal de Sergipe, Av. Marechal Rondon, S/N, 49000-000 S˜ao Crist'ov˜ao, SE, Brazil  \n76 Institute of Astronomy, KU Leuven, Celestijnenlaan 200D, B-3001 Leuven, Belgium  \n- 77 Center for Astrophysics and Space Astronomy, Department of Astrophysical and Planetary Sciences, University of Colorado, 389 UCB, Boulder, CO 80309-0389, USA\n- 78 Department of Astronomy, University of Florida, Bryant Space Science Center, Stadium Road, Gainesville, FL 32611, USA  \n79  \nInstituto de Astrof'ısica, Pontificia Universidad Cat'olica de Chile, Av. Vicu˜na Mackenna 4860, 782-0436 Macul, Santiago, Chile  \n80  \nInstituto de Astronom'ıa, Universidad Cat'olica del Norte, Av. Angamos 0610, Antofagasta, Chile  \n81 Department of Physics, Salisbury University, Salisbury, MD 21801, USA  \n- 82 Departamento de F'ısica, Facultad de Ciencias, Universidad Nacional Aut'onoma de M'exico, Ciudad Universitaria, CDMX, 04510, M'exico  \n83 Departamento de Astronom'ıa, Universidad de Concepci'on, Casilla 160-C, Concepci'on, Chile  \n84  \nSchool of Physics and Astronomy, University of St Andrews, North Haugh, St Andrews KY16 9SS, UK  \n85 Exzellenzcluster ORIGINS, Boltzmannstr. 2, D-85748 Garching, Germany  \n86 Department of Physics and Astronomy, West Virginia University, 135 Willey St, Morgantown, WV 26506, USA  \n87 Center for Gravitational Waves and Cosmology, West Virginia University, Chestnut Ridge Research Building, Morgantown, WV 26505, USA", 'ABSTRACT': "The eighteenth data release of the Sloan Digital Sky Surveys (SDSS) is the first one for SDSS-V, the fifth generation of the survey. SDSS-V comprises three primary scientific programs, or 'Mappers': Milky Way Mapper (MWM), Black Hole Mapper (BHM), and Local Volume Mapper (LVM). This data release contains extensive targeting information for the two multi-object spectroscopy programs (MWM and BHM), including input catalogs and selection functions for their numerous scientific objectives. We describe the production of the targeting databases and their calibration- and scientifically-focused components. DR18 also includes ∼ 25,000 new SDSS spectra and supplemental information for X-ray sources identified by eROSITA in its eFEDS field. We present updates to some of the SDSS software pipelines and preview changes anticipated for DR19. We also describe three value-added catalogs (VACs) based on SDSS-IV data that have been published since DR17, and one VAC based on the SDSS-V data in the eFEDS field.  \nKeywords: Surveys (1671), Astronomy databases (83), Astronomy data acquisition (1860), Astronomy software (1855)", '1. THE FIRST TWO DECADES OF THE SLOAN DIGITAL SKY SURVEYS': "This paper describes the eighteenth data release of the Sloan Digital Sky Survey (SDSS) and the first data release of SDSS-V.  \nSince its operations began in 1998, SDSS has been taking near-continuous observations of stars, galaxies, and quasars, and other objects, spanning from our solar system to the early days of the Universe. The first phase, SDSS-I (York et al. 2000), imaged over 8000 deg 2 of the sky in the ugriz filters and collected optical spectra  \nof more than 700,000 objects. SDSS-II completed the legacy imaging survey and added a dedicated supernova imaging survey (Frieman et al. 2008) and a spectroscopic survey of ∼ 230,000 Milky Way stars (SEGUE; Yanny et al. 2009).  \nSDSS-III (Eisenstein et al. 2011) focused entirely on spectroscopy and comprised an extension of SEGUE (SEGUE-2; Rockosi et al. 2022); a radial-velocity exoplanet survey (MARVELS; Ge et al. 2008); a clustering survey of galaxies and intergalactic gas in the distant universe (BOSS; Dawson et al. 2013), which required  \nan upgrade to the optical spectrographs (Smee et al. 2013); and an infrared survey of Milky Way and Local group stars (APOGEE-1; Majewski et al. 2017), which introduced infrared spectrographs to the suite of SDSS instrumentation (Wilson et al. 2019). SDSS-IV (Blanton et al. 2017) included a significant expansion of the APOGEE survey (APOGEE-2; Majewski et al.in prep), including the deployment of a new APOGEE-S spectrograph for observations with the 2.5m DuPont telescope at Las Campanas Observatory (LCO), as well as an extension of BOSS observations to previously understudied redshifts (eBOSS; Dawson et al. 2016), and an optical IFU survey of the gas and stellar properties of low-redshift galaxies (MaNGA; Bundy et al. 2015).  \nContinuing in this tradition, SDSS-V (Kollmeier et al. 2017, Kollmeier et al. in prep.) constitutes a major innovation step in science scope and hardware. It comprises three primary scientific surveys, called 'mappers': the Milky Way Mapper (MWM; Johnson et al. in prep.), the Black Hole Mapper (BHM; Anderson et al. in prep.), and the Local Volume Mapper (LVM; Drory et al. in prep.). See § 2, § 6, and § 7 for more details.  \nA hallmark of the SDSS family of surveys is the regular release of high-quality, well-documented, and ready-usable data to the entire world. Beginning with the Early Data Release (Stoughton et al. 2002), SDSS helped usher in the era of 'open science' through its regular data releases. This practice has proven fruitful for the astronomical community, enabling a very broad scientific reach and impact. The final data release of SDSS-IV was DR17, in December 2021 (Abdurro'uf et al. 2022). As of November 2022, SDSS data (across all survey phases) have been cited in more than 11,000 refereed papers, with over 650,000 citations. Stalzer & Mentzel (2016) named SDSS as one of the most influential data sets, even beyond astronomy and physics. SDSS data are also used in numerous educational contexts, from young schoolchildren to undergraduate and graduate students, especially through its Voyages and SciServer platforms 1 .  \nOne of the primary reasons for the widespread use of SDSS data is the collaboration's commitment to highquality, user-friendly documentation to accompany each data release (e.g., Weijmans et al. 2019). SDSS-V continues that core practice with DR18, as summarized in this paper. In § 2, we briefly summarize SDSS-V's scientific and hardware components. In § 3-4, we outline the scope of DR18 and how to access the information. § 5 describes the multi-object spectroscopic (MOS)  \ndatabases and targeting software, while § 6, § 7, and § 8 detail the MOS Milky Way Mapper, Black Hole Mapper, and 'open fiber' programs, respectively. § 9 describes the spectra that are released in DR18, and § 10 focuses on new and modified software. § 11 contains the Value-Added Catalogs released since DR17. Finally, § 12 summarizes all of this information and looks forward to the anticipated contents of DR19.", '2. SDSS-V: STATUS AND SCIENCE OBJECTIVES': "In this section, we provide a brief summary of the SDSS-V program at the time of this data release. Many of these elements have been described elsewhere (e.g., Kollmeier et al. 2017) and will be described in greater detail in companion papers, including Kollmeier et al. (in prep). We provide this information here as a standalone snapshot at this important survey milestone.  \nSDSS-V sets out to be the first astronomical survey to provide all-sky, multi-epoch spectroscopy in the optical and infrared. Its scientific goals and targets are grouped into three top-level 'Mapper' programs. The Milky Way Mapper (MWM; § 6) is mapping the stellar populations and chemo-dynamics of the Milky Way to understand its evolution, and is probing stellar physics and stellar system architectures by collecting optical and infrared spectra of stars in the Milky Way and the Magellanic Clouds. The Black Hole Mapper (BHM; § 7) is studying the physics of black hole growth through timedomain spectroscopy and is providing spectra for extragalactic X-ray-luminous sources from eROSITA (Merloni et al. 2012; Predehl et al. 2021), using optical spectra across the sky. The Local Volume Mapper (LVM) is examining gas emission, star formation, and stellar/interstellar energy exchange processes in the Milky Way and beyond, at unprecedented scales using ultrawide-field optical IFU spectroscopy.  \nMWMand BHM are designed to use the multi-object spectroscopy (MOS) infrastructure of SDSS-V, which includes the Sloan 2.5 m telescope at Apache Point Observatory (APO) in New Mexico, USA (Gunn et al. 2006) and the du Pont 2.5 m telescope at Las Campanas Observatory (LCO) in Chile (Bowen & Vaughan 1973). Obtaining homogeneous, all-sky spectral survey data at both optical and infrared wavelengths requires near-identical sets of optical and near-infrared fiber spectrographs in both hemispheres. For SDSSV, one of the optical BOSS spectrographs was moved from APO to LCO, so that each site is now equipped  \nwith a pair of APOGEE and BOSS instruments 2 . The central new hardware component for MOS observations in SDSS-V is the implementation of a focal plane system (FPS) with robotic fiber positioners (Pogge et al. 2020), which replaces the plug-plate system and enables efficient, single-epoch pointings with ∼ 15 minute exposure times. The adoption of the FPS, in turn, required a new three-element corrector for the Sloan telescope (Barkhouser et al. 2022).  \nFor the LVM, SDSS-V is building an entirely new facility at LCO to enable ultra wide-field IFU observations across ∼ 1,000 deg 2 . The Local Volume Mapper Instrument (LVM-i) builds upon replicated instrument concepts from DESI (Perruchot et al. 2018) and the successful IFU technology developed as part of SDSSIV/MaNGA. To meet the survey science requirements, LVM-i will comprise a set of four 160 mm telescopes coupled via fiber IFUs to three spectrographs providing full coverage of the optical waveband, all housed in a new dedicated enclosure (Herbst et al. 2020).", '3. SCOPE OF DATA RELEASE 18': "The main focus of DR18 is to lay the groundwork for future SDSS-V releases by presenting the updated access paths, data models, new targeting strategies, and other structures that will be used in DR19 and beyond (Table 1).  \nDR18 consists primarily of targeting information (algorithms and databases) for the MWM and BHM programs ( § 5). These catalogs comprise 269.5 GB of data in MOS TARGET DIR (Table 2). They also introduce the concept of a 'carton', a new organizational unit for SDSS observations. A carton is a set of targets that results from a specific target selection algorithm, designed to advance certain science goals. Examples of cartons include white dwarfs selected from Gaia -SDSS catalogs for MWM, and reverberation mapping targets for BHM. Cartons will play a large role in understanding the SDSS-V targeting strategy, target selection algorithms, and eventual full sample. They are discussed in more detail in § 5.2, and lists of MWM and BHM cartons are given in Tables 3 and 4, respectively. Cartons are grouped into 'programs', which are also columns in the  \n2 Details of APOGEE spectrographs: https://www.sdss. org/instruments/apogee-spectrographs/ and details of BOSS spectrographs: https://www.sdss.org/instruments/ boss-spectrographs/. Within SDSS-V, one will frequently encounter references to 'BOSS spectra'. This term always means 'spectra obtained with one of the two BOSS spectrographs', rather than 'spectra obtained as part of the SDSS-III BOSS (or SDSS-IV eBOSS) project'.  \ntarget tables that refer to broader science cases whose goals will be met by targets from one or more cartons.  \nA small number of new BOSS spectra are being made available as part of eFEDS (Brunner et al. 2022), an eROSITA follow-up program ( § 9.1). These add a volume of 301.9 GB to BOSS SPECTRO REDUX , including the ∼ 25k spectra. Accompanying these spectra is a new value added catalog (VAC), which contains updated redshifts and classifications (see § 11.2). DR18 also contains new software routines and updates to existing SDSS software ( § 10), particularly the BOSS spectral reduction package ( § 10.1).  \nFinally, all previous SDSS data are also available through the SDSS portals without any changes or additional processing, essentially summarized in DR17 (Abdurro'uf et al. 2022). Newly available as part of DR17, coincident with DR18, are two new VACs based on DR17 data, as well as an earlier DR15-based VAC that has been updated with data from DR17. These VACs are described in greater detail in § 11.1.", '4. ACCESSING THE DATA': 'There are numerous ways to access the SDSS DR18 data products, summarized on the SDSS website 3 and on the data release website 4 . As in previous phases of SDSS, SDSS-V provides a searchable database for the Catalog Archive Server (CAS), using SkyServer 5 , with both SQL and Jupyter notebook interfaces. The Science Archive Server (SAS) is well-suited for directly downloading flat files, including spectra. Both the CAS and SAS are cumulative systems, with some data products replacing or extending data from previous releases, generally speaking. Examples of data products that can be replacements (not in DR18) include spectroscopic reductions and their associated parameters and Value-Added Catalogs. In these cases, only the latest version is included in the data release, but all previously released versions are available at their original locations. An example of data products that are cumulative is the raw data transferred from the observatories for each night of observations.  \nThe best way to access a particular data product will depend on the data product itself and the anticipated use case. We recommended to use the CAS when accessing the MOS targeting data described in § 5.1, since this product was originally created as a relational database.  \nT able 1. Summary of DR18 Con ten ts  \nData Access  \nDescription  \nItem  \nT argeting Information 1  \nrg/dr18  \ner.sdss.o  \nttps://skyserv  \nh  \n)  \n5.1  \n§  \n(  \ncatalogs  \nnput  \ni  \nof  \nh  \nCross-matc  \ncatalog  \nmos  \ner.sdss.org/dr18  \nttps://skyserv  \nh  \ncatalogs)  \ncore  \nfor  \n2  \nable  \nT  \n,  \n5.1  \n§  \n(  \ncatalogs  \nInput  \ncatalogs  \nX  \nmos  \ner.sdss.org/dr18  \nttps://skyserv  \nh  \n)  \n5.2  \n§  \n(  \ncartons  \nmore  \nor  \none  \nof  \ncriteria  \nn  \nselectio  \nthe  \ng  \nmeetin  \njects  \nOb  \ntarget  \nmos  \ner.sdss.org/dr18  \nttps://skyserv  \nh  \n)  \n5.2  \n§  \n(  \nts  \nrequiremen  \national  \nobserv  \nand  \ncartons,  \ntargets,  \nlinking  \nable  \nT  \nmos carton to target  \ner.sdss.org/dr18  \nttps://skyserv  \nh  \n)  \n8  \n§  \n,  \n7  \n§  \n,  \n6  \n§  \n,  \n5.3  \n§  \n,  \n5.1  \n§  \n(  \ncartons  \nSDSS-V  \nof  \nable  \nT  \ncarton  \nmos  \nectra  \nSp  \nDirectories and data mo dels are in § 9.1.2  \n)  \n9.1  \n§  \nand  \n7.3  \n§  \n(  \nsources  \nA-selected  \nOSIT  \neR  \nof  \nectra  \nsp  \nOptical  \nectra  \nsp  \neFEDS', 'V alue-Added Catalogs (V A Cs) SDSS-IV V A Cs Based on SDSS-IV data ( § 11.1 , T able 6 ) SDSS-V V A C Based on SDSS-V (eFEDS) data ( § 11.2 , T able 6 )': 'Note -  \n1 These are a subset of th e total individual targeting tables a v ailable f rom the CAS. The full list can b e see n in the CAS Sc hema  \nBro wser: h ttps://skyserv er.sdss.org/dr18/MoreT o ols/bro wser .  \nThe corresponding fits files on the SAS are primarily for archival purposes. Access to the eFEDS spectra is described in § 9.1.3; these spectra are also available for visual inspection in the Science Archive Webapp at https://dr18.sdss.org/optical/.  \nEach type of data file on the SAS has an associated data model, which describes its format and content. SDSS-V is developing extensions to the existing data model products to include better accessibility in formats other than the current static html , such as yaml , json , and backward compatibility with classic html . For DR18, all data models can be found at https://data.sdss.org/datamodel/.  \nThe SDSS DR18 website has numerous tutorials and examples available to access and interact with both the MOS targeting data and the eFEDS spectra released in DR18. See https://www.sdss.org/dr18/tutorials/ for more information.', '5. MULTI-OBJECT SPECTROSCOPY TARGETING': "The primary data products in DR18 are the underlying, cross-matched catalog of objects targeted by SDSSV and the list of targets. In this section, we describe how these data are organized into cross-matched catalog database tables and target tables. Throughout DR18, we use 0.5 to indicate the version of the catalog crossmatching process ( § 5.1). Variants of the target selection of individual cartons ( § 5.2) using this cross-match are versioned as 0.5.X , where ' X ' varies between cartons. A set of cartons and carton targeting versions is referred to as a 'targeting generation', which is tracked similarly as 0.5.X . Targeting generation 0.5.3 is the one released in DR18.", '5.1. Catalog Database Tables and Cross-Matching': "Previous generations of SDSS relied almost exclusively on a single imaging catalog for targeting. In the optical, the SDSS imaging survey (Abazajian et al. 2009; Padmanabhan et al. 2008) formed the basis for targeting, while in the H -band, the 2MASS all-sky survey was used (Skrutskie et al. 2006). For SDSS-V, this approach is no longer practical because of the need for all-sky, deep optical imaging and the desire to observe stars in both the optical and the infrared. Gaia imaging does not go deep enough in the extragalactic sky, while even the union of SDSS imaging, PanSTARRS imaging, and other wide-field imaging do not cover the full sky at the necessary wavelengths.  \nTherefore, to ensure that each object in the sky of relevance to SDSS-V has a unique identifier, regardless of how many imaging catalogs it appears in, we created our own targeting database. All SDSS-V multi-object spectroscopy (MOS) targets (i.e., all targets for MWM and  \nBHM) are stored in a suite of database tables, which contains both a unified list of all sources within a set of crossmatched input catalogs and the targeting classifications of those sources. This section describes how the catalogs are stored; § 5.2 describes how the targeting classifications are stored.  \nFigure 1 shows a cartoon representation of the primary database tables and workflows presented in this section. The mos catalog table is the central unified list of sources. It was created from the set of spatially cross-matched core input catalogs, which are listed in Table 2 and shown in yellow in Figures 1 and 3. We have a set of additional catalogs used in targeting whose entries are associated with entries in the spatially crossmatched catalogs; these are the tables highlighted in blue in Figures 1 and 3. The database in DR18 stores this set of catalogs and the associations between objects within them.  \nThe mos catalog table contains only a minimum of information for each object: only the positional information and the catalogid identifier, which is an internal ID used by the SDSS-V databases to uniquely identify each source. All other information about the sources is stored in the individual cross-matched and targeting catalogs. Each catalogid is associated with one or more entries within these original catalogs. For 17 of the original input catalogs, the association between mos catalog and the original catalog is expressed as shown in Figure 2, using a join table mos catalog to X for each input catalog ' mos X '. As above, the list of all original catalogs cross-matched in this fashion is in Table 2, along with the primary key used for each (i.e., the column labeled ' X id ' in Figure 2).  \nThe initial basis for mos catalog is the TESS Input Catalog v8 (TIC; Stassun et al. 2019), which is all-sky and uses both Gaia DR2 and 2MASS to identify objects 6 . Then, cross-matching follows a three-phase procedure for each of the subsequent input catalogs listed in Table 2, which can include both point and extended sources. First, we use existing literature cross-matches included with the catalog information to identify physical targets that already exist in the mos catalog table. For those, a new entry is added to the appropriate mos catalog to X table that references the matched catalogid and the unique identifier in the input catalog.  \nFigure 1. Cartoon diagram of the relationships between several key database tables and of the workflow between sky sources and observed targets ( § 5.1-5.2). The objects colored yellow, blue, pink, and purple correspond to the same types of tables in Figures 2-4. The green color has been repurposed to highlight the 'observational' section of the workflow, where candidate targets are down-selected and grouped into observable designs ( § 5.2). Left: the pink mos catalog is built as a superset of the yellow core input catalogs ( § 5.1, Table 2), whose circles are approximately scaled here to the size of the catalog. The blue 'additional catalogs' ( § 5.1) provide supplementary information to sources in mos catalog . Right: the small purple circles represent the many individual cartons ( § 5.2), which specify both target selection criteria and observational requirements. The potential targets satisfying the selection criteria, along with the observational requirements (stored in mos carton to target ) are used by the robostrategy code (Blanton et al., in prep) to produce observable designs, previously for plates (Covey et al., in prep) and now for the FPS robots.  \n<!-- image -->  \nFigure 2. Relationships between the cross-matched mos catalog table and the original source input catalogs ( § 5.1). There are 17 source input catalogs that are linked to mos catalog through the structure shown above, with 'X' representing the name of the original catalog (Table 2).  \n<!-- image -->  \nFor targets in the input catalog that do not have an available association with mos catalog , we perform a cone search around the coordinates of each target and find the associated mos catalog entries within the search radius. We use a default 1 arcsec search radius, but this value is sometimes modified to match the spatial resolution of the input catalog. All the  \ncone-search-matched catalogid entries are associated with the input catalog target via the corresponding mos catalog to X table. The match with the smallest on-sky separation is marked as the 'best' match 7 by setting the best column in the mos catalog to X table to True . Finally, targets in the input catalog that cannot be spatially cross-matched are considered new physical objects and added to mos catalog and mos catalog to X with a new unique catalogid .  \nFor some of these 17 catalogs, the database contains further associations between them and the additional  \nTable 2. Cross-matched input catalogs for the catalog database ( § 5.1)  \ncatalogs used in targeting. Figure 3 shows these other catalogs and how they are associated in the database with the cross-matched catalogs.  \nDR18 contains the catalog cross-matching version v0.5 , which was used for targeting at the beginning of MOS observations in SDSS-V. Due to the size of the databases involved, the tables in the released DR18 version only contain sources that were ultimately identified with potential targets (i.e., are in one or more cartons). DR18 also excludes some X-ray catalogs from eROSITA that were used for targeting in v0.5 but not yet made public. Due to an error, DR18 also excludes tables associated with the TESS Objects of Interest, the Spitzer /MIPSGAL program (Gutermuth & Heyer 2015), and the Gaia ASAS-SN Classical Cepheid sample (Inno et al. 2021); these tables will be included in DR19.", '5.2. Target Database Tables and MOS Cartons': "Drawing on the catalog database and the information stored in the linked catalogs described above ( § 5.1), the target selection software determines which objects should be targeted for spectroscopy using the selection criteria and other properties of the target cartons. The target selection criteria are described in later sections, on the website, and in other program papers; here we only describe how the information is organized.  \nAfter the target selection software is run, the targeting database contains a set of targets and a set of cartons. Figure 4 shows how this information is stored for a generalized subset of the database tables. The associations between targets and cartons are stored in the mos carton to target table. Each carton is associated with all of the candidate targets that satisfy the selection criteria for the carton. Each target is associated with one or more cartons.  \nFor example, consider a star that has a detection in Gaia DR2. This star will appear in the TIC v8, and thus will have an entry in mos catalog . If this star satisfies the selection criteria for any carton, it will also appear in mos target , with a corresponding entry in mos carton to target . If this star satisfies the criteria for multiple cartons, then multiple entries in mos carton to target will be associated with the star's single entry in mos target . Each mos carton to target entry is also associated with an entry in the mos carton table, which gives the name of the carton and other information.  \nEach mos carton to target entry has an associated set of entries cadence, value , and priority -that are used in the process of determining the survey strategy and fiber assignment process. The cadence describes how the target should be observed (number of epochs, number of observations per epoch, and observing condi-  \nFigure 3. Relationships between cross-matched mos catalog table (pink), original source catalogs (yellow) and additional catalogs used for targeting (blue), for the cases where additional such catalogs exist. mos catalog contains the full crossmatched list of sources, and it is associated with the original source catalogs through join tables (green) in the manner described in Figure 2 and § 5.1. Additional catalogs can be joined as shown to the original source catalogs, and thereby to the mos catalog table, as shown. For clarity, only the columns necessary for table joins are shown in this diagram.  \n<!-- image -->  \ntions). The cadence pk values allow a join to a cadence table with the cadence name and other parameters associated with it.  \nThe value expresses how important the target is to the overall objectives of the MOS program, which is used in the determination of the overall survey strategy. The priority expresses the order in which targets should be assigned to fibers during fiber assignment in a given pointing. These quantities are more fully explained in the robostrategy paper (Blanton et al. in prep).  \nEach carton also has an assigned category , which can be one of science , sky boss , standard boss , sky apogee , or standard apogee . The first category indicates science targets, and the others are different types of calibration targets ( § 5.3-5.4).  \nAmong the science target cartons, there are those whose observations are required for the stated success  \nof SDSS-V science, as laid out in the survey's science requirements document ('SRD'). These cartons tend to have descriptive names. The cartons that arose from an initial call within the SDSS-V collaboration for 'open fiber' targets have carton names starting with opentargets ). There is also a set of filler targets for spare fibers. The released tables in DR18 do not unambiguously identify which cartons are SRD, open, or filler (although the information can often be approximately guessed from the carton names), because this identification is associated with the fiber assignment results, which will not be released until DR19.", '5.3. Standard star cartons': "5.3.1. APOGEE standard stars  \nThe standard stars for APOGEE observations are used primarily to correct telluric absorption by Earth's  \nFigure 4. Association of catalogid s with targeting information. Each catalogid that is selected by one or more cartons is given an entry in the mos target table. For each carton that selects it, there is a mos carton to target entry. Each entry is associated with one target and one carton, and specifies the cadence, instrument (BOSS or APOGEE), and other observing conditions. Further tables in the database define the properties of the cadences, the names of the instruments, and the names of the categories ( science , sky boss , standard boss , sky apogee , and standard apogee ).  \n<!-- image -->  \natmosphere. They are selected in a process very similar to that used for APOGEE-1 and APOGEE-2 observations, which aimed to select hot, blue stars (with few absorption lines of their own) distributed as evenly as possible across the field of view to allow for spatiallydependent telluric corrections (Zasowski et al. 2013; Zasowski et al. 2017).  \nThe carton ops std apogee contains these calibration stars, which are drawn from the 2MASS PSC (Skrutskie et al. 2006). They are restricted to have magnitude 7 < H < 11, color -0 . 25 < ( J -K s ) < +0 . 5, and magnitude uncertainties (JERR, HERR, KERR) of ≤ 0.1 mag. In addition, we applied the requirements that the 2MASS read flag be equal to '1' or '2', the quality flag for J , H , and K s be equal to 'A' or 'B', the galaxy contamination flag be equal to '0', the confusion flag be equal to '000', the extkey ID (linking to the 2MASS Extended Source Catalog; Jarrett et al. 2000) be Null , and the star lie at least 6 '' from its nearest 2MASS neighbor. From this subset of potential standard stars, the five bluest sources are chosen from each HEALPix NSIDE = 128 pixel (0.21 deg 2 pix -1 ; G'orski et al. 2005) as telluric standard stars.", '5.3.2. BOSS spectrophotometric standard stars': 'Spectrophotometric standard stars are used by the BOSS pipeline to calibrate the absolute and relative throughput of the instrument during science observations. The strategy for selecting BOSS standards in SDSS-V builds upon past experience from the SDSSIII/IV BOSS and eBOSS projects (see, e.g., Dawson et al. 2013, 2016). Selecting standards for the SDSS-  \nV program presents some new challenges: i) we need to select standard stars outside the footprint of the SDSS photometric imaging catalog, and ii) we need to reliably select standards along lines of sight that may be heavily reddened by Galactic dust. In order to satisfy the first challenge, we exploited wider area photometric and astrometric information from PanStarrs, the DESI Legacy Surveys, and Gaia. To mitigate the complications of extinction, we used the 3D reddening information provided by the TIC v8 catalog (Stassun et al. 2019).  \nBelow we briefly describe the target selection criteria for the various BOSS standards cartons used in early SDSS-V operations, which are released as part of DR18 (targeting generation v0.5.3 ).  \nThe ops std eboss carton is identical to the spectrophotometric standards used by the eBOSS survey (Dawson et al. 2016). These standards lie in the magnitude range 16 < r psf < 18 AB and so are most suitable for use in dark time. Use of these standards maintains an important continuity with archival SDSS spectroscopy, which is especially important when investigating the long term variations of QSOs ( § 7).  \nThe ops std boss ps1dr2 , ops std boss lsdr8 , and ops std boss gdr2 standard star cartons are based on PanStarrs1-DR2, Legacy Survey DR8, and Gaia DR2 photometry, respectively. For each carton, we use the empirically determined location of eBOSS standards within the dereddened color space of the given photometric system to train our new selection locus. Additional cuts on data quality, and in the parallax vs magnitude plane (via Gaia DR2), are applied to further clean outliers from the sample. Magnitude limits are applied such that these standards are appropriate for BOSS dark-time observations (approximately 16 < r psf < 18 AB, or 16 < G < 18 Vega). Additionally, the ops std boss gdr2 carton is limited to Galactic latitudes of | b | > 10 · . We estimate SDSS g psf , r psf , i psf , z psf magnitudes for each BOSS standard star target, transferring their native multi-band photometry into the SDSS system via color transforms derived from the ops std eboss sample.  \nAdditional BOSS standard cartons were developed to facilitate all-sky observations during bright time: ops std boss tic , ops std boss , and ops std boss red . These cartons fill in the regions of the sky that are not covered by the BOSS standard cartons described above, and they include brighter standards, to mitigate the potential impact of crosstalk from brighter science targets in the design. The ops std boss tic carton consists of likely F stars, selected via T eff and surface gravity cuts applied to TICV8 stellar parameters (Stassun et al. 2019). To provide  \nuniform coverage over the sky, targets are sorted into a NSIDE=128 HEALpix grid (0.21 deg 2 pix -1 ), and the 10 highest-gravity stars in each healpix are retained for the final carton. The ops std boss carton similarly targets F stars, but selected via cuts on Gaia parallax, color, and absolute magnitude. Finally, the ops std boss red carton is intended to provide standards even in the most heavily extincted sections of the Galactic midplane. This carton uses cuts on observed and dereddened Gaia+2MASS colors, as well as parallax, proper motion and reduced proper motion criteria to reduce contamination from non-F stars whose observed colors can be dereddened into the relevant areas of color-magnitude space.', '5.4. Sky fiber locations': "The data reduction pipelines for BOSS and APOGEE both require a number of fibers to be placed at 'sky' locations, which do not contain light from astrophysical sources and thus allow for the correction of the observed spectra for contamination by emission processes in Earth's atmosphere. The number and 'quality' of sky fibers per configuration is dependent on the type of observation to be performed. For example, for SDSS-V observations targeting faint extragalactic populations in dark time, we reserve 20% of the BOSS fibers for sky observations, and those locations must be empty of astrophysical sources down to the magnitude limit of the deepest wide area imaging that we currently have available. In contrast, observations of bright targets in bright time generally require fewer sky fibers, and can sometimes tolerate mild contamination from faint astrophysical sources. However, even with such reduced criteria, suitable sky fiber locations can be challenging to find in the densest Galactic plane fields.  \nWith these constraints in mind we have designed a hierarchy of sky fiber cartons, which collectively satisfy all SDSS-V FPS observational requirements. BOSS observations use three cartons: ops sky boss best , ops sky boss good , and ops sky boss fallback , and APOGEE observations draw on two cartons: ops sky apogee best , and ops sky apogee good .  \nFirst, the sky is divided into HEALPix NSIDE = 32 pixel 'tiles', comprising roughly 3.4 deg 2 pix -1 , which is approximately the area spanned by a single FPS configuration. Each tile is further divided into HEALpix NSIDE = 32768 pixels (41 arcsec 2 pix -1 ), the centers of which are considered candidate sky locations 8 . Each  \ncandidate sky location is then compared to a set of input catalogs (given below) and labeled valid (with respect to each comparison catalog, separately) if i) their NSIDE = 32768 HEALpixel contains no astrophysical objects in that catalog, and ii) they lie further than a magnitude-dependent separation from the nearest potentially contaminating astrophysical source. This minimum separation is computed as s ∗ = s + ( m thr -m ) β a , where s = 5 arcsec is a minimum radius floor and m thr is a fixed brightness threshold (14 mag). The a = 0 . 15 and β = 1 . 5 parameters control the scaling of the exclusion radius with brightness, and are set to conservative values. We consider the H , G , V total , r psf , and r model magnitudes for objects from the 2MASS PSC, Gaia DR2, Tycho2, Pan-STARRS1 DR2, and Legacy Survey DR8 catalogs, respectively (Skrutskie et al. 2006; Gaia Collaboration et al. 2018; Høg et al. 2000; Flewelling et al. 2020; Dey et al. 2019). Candidate sky locations lying near 2MASS extended sources (Jarrett et al. 2000) are considered to be valid if they lie outside the 'extrapolation/total radius' of the source. All of these candidate locations that are valid in one or more catalogs are stored in the catalogdb table skies v2 and serve as inputs for the cartons below.  \nThe highest quality sky carton for BOSS (i.e., suitable for darkest observations) is ops sky boss best . For this carton, we require locations to be valid in each of the 2MASS (point- and extended sources), Tycho2, and Gaia DR2 catalogs. Furthermore, selected sky locations must be within the Pan-STARRS1 or Legacy Survey DR8 survey footprints, and must not be contaminated by sources from either catalog. Somewhat less restrictive is the ops sky boss good carton, which drops the requirement to avoid Pan-STARRS1 and Legacy Survey DR8 sources, and so extends the list of available sky locations to the entire sphere, excepting an area of the Galactic bulge and the inner parts of the Magellanic Clouds. In order to provide sky fiber locations in those remaining regions, the ops sky boss fallback carton loosens the radial exclusion criteria, preferring locations that lie furthest from Gaia DR2 sources but requiring only that the sky location lies more than 3 '' from a Gaia DR2 or Pan-STARRS1 source, more than 5 '' from any 2MASS source, and more than 15 '' from any Tycho2 star.  \nFor APOGEE observations, the highest quality ops sky apogee best carton requires sky locations to be valid in each of the 2MASS (point- and extended sources), Tycho2, and Gaia DR2 catalogs. The lowerpriority ops sky apogee good carton is dedicated to finding the remaining least-bad sky locations in dense regions. These positions have a maximum nearest neigh-  \nbor brightness of H = 10, and candidates lying farthest from 2MASS contaminants are preferred.", '6. MILKY WAY MAPPER: SCIENCE PROGRAMS AND TARGET SELECTION': "The Milky Way can serve as a 'model organism' for understanding the physical processes that shape galaxies over an enormous rage of temporal and physical scales in the context of hierarchical cosmogony. The Milky Way Mapper (MWM) takes advantage of our unique perspective within the Milky Way to create an unprecedented high-resolution map of our Galaxy's stellar populations. MWM is observing stars formed in the dawn of the Galaxy through the present day, thoroughly sampling the H-R diagram and chemical abundance space. Through multi-epoch, multi-wavelength observations of single stars and stellar systems, MWM seeks to understand the evolution of the luminous constituents of the Galaxy and detect unseen compact objects and substellar objects.  \nMWM focuses on four connected themes:  \n- · Galactic Archaeology : We can reconstruct the deep history of the Milky Way through observing the number, masses, composition, ages, and motions of its stars and the structures that they create. Luminous red giants cover a large range of ages, from ∼ 1 Gyr and older. However, samples of red giants are insensitive to the history of intermediate-mass stars older than ∼ 1 Gyr. Such stars have turned into stellar remnants, mostly white dwarfs. Other sites of Galactic archaeology studied in open fiber programs ( § 8) in targeting generation v0.5.3 include the Galactic halo and the Magellanic Clouds.\n- · The Young Galaxy : The programs under Galactic Archaeology investigate the cumulative history of star formation, chemical enrichment, and radial migration of the Milky Way, as told through evolved stars across a range of masses. Young stars (here ∼ 5 -100 Myrs) fill in the early phases of lowmass stellar evolution and the full life cycle of massive stars. They provide a detailed and complete snapshot of the youngest generation in the Milky Way. In MWM, we systematically target low-mass young stars (YSOs) within ∼ 500 pc and all luminous, hot stars throughout the Galactic disk. Dust is relevant to not only the current structure of the Milky Way, but also how metals are incorporated into the ISM and thence into the next generation of stars. MWM takes advantage of dust and extinction indicators along lines of sight to its ob-  \nstars to map the dust and its properties in the disk.  \n- · The High Energy Galaxy : Galactic sources of X-ray emission include compact object accretors, young stellar objects, and flaring stars, all objects of intense interest for the other themes here as well. The eROSITA mission is measuring X-ray fluxes for millions of point sources in the Galaxy. However, to identify and explore the physical nature of such objects, optical and/or infrared spectra rich in absorption and emission features are critical.\n- · Stellar Physics and Stellar Systems : Undergirding all of MWM's Galactic explorations are the properties of stars and stellar systems. We begin these investigation close to home - in the solar neighborhood, the only place in the universe where it is practicable to obtain a spectroscopic census of stars down to the hydrogen burning limit.  \nTo reliably predict the age, evolutionary state, nucleosynthesis, internal mixing, and end state of stars, we need to understand their structure. Astereoseismology - the study of how waves propagate through stellar interiors - provides a powerful tool for this work, especially when combined with stellar and dynamical parameters from spectra. MWM is targeting oscillating red giant and hot stars. In the latter case, we are focusing on OBA stars in massive eclipsing binaries.  \nMost stars orbit other stars. MWM is unique among current large spectroscopic surveys in targeting a vast range of stellar types for time-domain radial velocity observations, including YSOs, OB stars, WDs, and red giants. Particular attention is also paid to compact binaries, which are binary systems where at least one component is a WD, neutron star, or black hole, and to stars observed at high cadence for planet transits. By increasing the number of epochs, MWM is increasing the probability of orbit reconstruction with the goal of probing long baselines ( > 8 years) and the brown dwarf desert.  \nThese top-level science goals are achieved by observing an anticipated ∼ 5 million stars, with the different target categories structured in a set of target cartons. Each carton has a well-defined selection function to enable subsequent population modeling (Rix et al. 2021). These cartons are summarized in Table 3, with complete selection functions provided in Appendix A and on the  \nDR18 website 9 . It is important to note that these target selections are the input into the observational design code ( § 10). The final targets that will actually be observed are an as-yet-unknown subset of these selections. See Johnson et al. (in prep) for a complete description of MWM's goals and targeting.  \nDR18 contains substantial targeting information for MWM, including the input catalogs used to generate potential target lists, the selection functions for the numerous cartons, and the data models for the anticipated output files. Users anticipating the first spectroscopic data release in DR19 can use this information to prepare for analysis of the DR19 data. We confine our discussion here to the v0.5.3 targeting scheme, deferring presentation of cartons added in subsequent targeting schemes (e.g., for validating stellar parameters, observing Gaia binaries, and other expansions and improvements) to the future MWM overview and DR19 papers. Thus, the subsections below enumerate the specific programs, and their constituent cartons, designed under the v0.5.3 targeting strategy to address the scientific goals above.", '6.1. Galactic Genesis': "Galactic Genesis is the flagship program of the MWM, with near-infrared (APOGEE) observations of over 4 million stars planned. Galactic Genesis's central science goal to obtain a fine sampling of the chemo-orbital distribution of stars across the entire radial extent of the Milky Way, probing the Galactic plane, the central regions of our Galaxy, and the far side of the disk. To do this, Galactic Genesis targets luminous red giants, above the red clump, where the multi-million sample size with dust-penetrating APOGEE observations provides a decisive advantage over other surveys.  \nAll of the Galactic Genesis targets are contained in the mwm galactic core carton.", '6.2. White Dwarfs': 'White dwarfs (WDs) are tracers of Galactic star formation, progenitors of type Ia supernovae, important end products of both single and binary star evolution, and important cosmic physics laboratories (e.g., for the formation of strong magnetic fields). Gaia has recently produced enormous, well defined samples of WDs ( ∼ 250,000 objects). SDSS-V is enlarging the subset of these WDs that have complementary spectroscopy (especially in the southern hemisphere) and also providing multi-epoch observations for empirical input on the bi-  \nry WD merging channels towards SNe Ia and other remnant products (e.g., Chandra et al. 2021).  \nAll of the MWM WDs targeted for this program are contained in the mwm wd core carton.', '6.3. Solar Neighborhood Census': "MWM's Solar Neighborhood Census (SNC) program targets a volume-limited sample of stars with the goals of cataloging low-luminosity stellar populations. While not technically 'complete', the SNC will provide highquality, two-epoch BOSS or APOGEE spectra of > 10 5 stars within 100 pc and within 250 pc. The most complete census will be within 100 pc. However, there are few stars hotter than K types that close to the Sun, so a sample of stars out to 250 pc away is also targeted to enable a reliable match to higher luminosity populations.  \nThe SNC targets span four cartons, all beginning with mwm snc : mwm snc 100pc apogee , mwm snc 100pc boss , mwm snc 250pc apogee , mwm snc 250pc boss , where the latter part of the carton names indicate the volume size and instrument.", '6.4. Young Stellar Objects (YSOs)': 'The MWM YSO program targets the pre-mainsequence phase of low-mass stars. These objects are key to understanding the early phases of low-mass stellar evolution, on what orbits stars are born, and how they disperse from their clustered birth sites to become field stars. The YSO program selects objects via their position in the color-magnitude diagram (CMD), optical/IR SED, or variability. APOGEE spectra then provide stellar parameters and velocities, while BOSS spectra provide indicators of youth, such as Li absorption and H α emission. Kounkel et al. (submitted) presents a complete discussion of the target selection rationale and on-sky validation.  \nCartons that fall under the YSO program have names beginning with mwm yso , a third label indicating their selection method, and a fourth label indicating the instrument used (either apogee or boss ). The shorthand labels for the selection methods are cluster , cmz , disk , embedded , nebula , pms , and variable . For example, YSO targets selected based on their variability and observed with the APOGEE instrument are contained in the mwm yso variable apogee carton. The full selection functions for these methods are detailed in Appendix A.', '6.5. OB Stars': 'Massive stars on the main sequence are unambiguously young because of their short hydrogen-burning  \nlifetimes. They are excellent tracers of the recent star formation throughout the disk (e.g., Zari et al. 2021) and they are most likely luminous companions to black holes and neutron stars, objects that were once even more massive stars. These hot stars are also the dominant ionizers of the interstellar medium. The MWM OB program targets all stars brighter than G = 16 that are also likely to be hotter than ∼ 8000 K.  \nThe massive stars in this program fall into two cartons: mwm ob cepheids , targeting known Cepheid stars (Inno et al. 2021), and mwm ob core , targeting a larger sample of OBA stars across the MW and Magellanic Clouds.', '6.6. Galactic eROSITA Sources': 'In addition to the spectroscopic follow-up of highredshift X-ray sources from eROSITA ( § 7.2), the Galactic eROSITA sources program in MWM is targeting likely Milky Way X-ray sources, including accreting compact objects, YSOs, and flare stars. The optical and IR counterparts of these sources were identified by the eROSITA Stars and Compact Objects working groups and are being observed with the APOGEE and/or BOSS instrument(s), depending on the H -band or G -band magnitude, for source characterization.  \nThe Galactic eROSITA program targets comprise three cartons: mwm erosita stars , for likely stellar coronal emitters, and mwm erosita compact gen and mwm erosita compact var for likely compact object accretors, using two different methods for finding the likeliest optical counterpart.', '6.7. Massive Eclipsing Binaries': 'The main-sequence structure of massive stars, including the size of their convective cores, is intimately linked to their (eventual) remnant mass and other properties. The Massive Eclipsing Binaries (EBs) program uses asteroseismic and photometric data to identify the likeliest double-lined spectroscopic EBs with pulsational variability, among OBA stellar types.  \nThese targets are contained in the manual mwm tess ob carton.', '6.8. Binary Systems': 'The APOGEE-1 and -2 surveys contributed to binary studies both through statistical studies of large samples (e.g., Price-Whelan et al. 2020; Mazzola et al. 2020) and through reconstructing orbits (e.g., Washington et al. 2021). In MWM, the orbital size and mass range spanned by targets in the OB Stars and YSO programs will be increased by serendipitous observations of previously-observed stars that meet the Galactic Genesis criteria (see above). The Binary Systems program is  \nfurther enhancing this sample of stellar and substellar companions of stars across the HR diagram by investing fibers to extending time baselines of red giants, subgiants, and M dwarfs. This program exclusively uses the APOGEE spectrograph because of its superior spectral resolution and improved RV precision.  \nTargets in this program fall in one of two cartons: mwm rv long fps , for stars with existing multi-epoch observations from APOGEE, and mwm rv short fps , for stars without these earlier observations.', '6.9. Compact Binaries': 'Spectra of compact binary systems are frequently marked by non-stellar emission - such as X-ray, UV, or H α flux - that can probe mass transfer or other nonthermal processes. The Compact Binaries program is observing a large number of likely compact binary systems, identified through different combinations of CMD position, UV excess, and previous association with a cataclysmic variable (from the AAVSO 10 ).  \nThese different combinations of selections are reflected in the many cartons contained in the Compact Binaries program. All of the carton names begin with mwm cb or manual nsbh , followed by additional labels indicating the selection method and (in some cases) the instrument used for the MWM observations. The shorthand labels for the selection methods are 300pc , cvcandidates , gaiagalex , and uvex[1-5] . The full selection functions for these methods are detailed in Appendix A.', '6.10. Planet Hosts': "Understanding the conditions that impact a star's likelihood of hosting planets, and the properties of the planetary orbits and the planets themselves, is essential for understanding planet formation and solar system evolution. The Planet Hosts program targets TESS stars with and without associated TESS Objects of Interest (TOIs). These will be observed with the APOGEE instrument to provide stellar parameters and detailed stellar abundances.  \nThe single carton in this program is called mwm tess planet .", '6.11. Asteroseismic Red Giants': "For stars on the red giant branch (RGB), asteroseismology arguably provides the gold standard of stellar mass and surface gravity measurements, but maximizing its power requires additional input from spectroscopy (such as stellar metallicity). The goal of the Asteroseismic Red Giants program is to obtain spectra for stars  \nwith asteroseismic signals, especially those observed by TESS. The start of SDSS-V overlapped with the nominal mission of the TESS satellite, so this program targets bright RGB stars throughout most of the sky (avoiding the Galactic plane), under the expectation that some large fraction of them would eventually have detectable oscillations. This simple selection function will enhance the legacy value of this program's sample.  \nThe single carton in this program is called mwm tessrgb core .", '6.12. Dust': "Interstellar dust presents both a challenge and an opportunity in studying the structure and history of our Galaxy. For example, rigorous modeling of the Milky Way's structure, based on stellar observations, requires (approximate) knowledge of the 3D extinction distribution, as seen from the Sun. Such a map then permits dust-corrected estimates of stellar distances for stars with spectroscopic luminosity estimates but poor parallaxes, but also valuable information on the 3D structure of the cold interstellar medium. MWM's Dust program is obtaining spectra for mapping distribution of the density and properties of dust (such as R V ; e.g., Schlafly et al. 2016). Those spectra will of also provide information on the column density and kinematics of the ISM via the diffuse interstellar bands (e.g.. Zasowski et al. 2019). The targets for this program are RGB stars selected to 'fill in' the regions of low extinction avoided by the Galactic Genesis program, to achieve an even sampling of the Milky Way's dust with the total MWM sample.  \nThe single carton in this program is called mwm dust core .", '6.13. Science Validation': 'The only carton in this program in the v0.5.3 targeting generation is mwm legacy ir2opt , which is a filler carton to obtain BOSS spectra of stars observed in APOGEE-1 and -2. The stellar parameters from the higher-resolution APOGEE spectrum of a given star are used to provide labels for the BOSS spectrum, facilitating data-driven modeling and cross-calibration of the BOSS spectra. Future targeting generations will include additional cartons targeting stars with known fundamental parameters and stars targeted by other large spectroscopic surveys.', '7. BLACK HOLE MAPPER: SCIENCE PROGRAMS AND TARGET SELECTION': "The Black Hole Mapper (BHM) sets out to better understand the growth of supermassive black holes at the centers of galaxies, through both time-domain spectroscopy of quasars and other AGN, and the first large-area optical spectroscopic follow-up of the newly available eROSITA X-ray survey. In its quasar timedomain program, SDSS-V will provide orders of magnitude advances in both time baseline and sample sizes. The BHM time-domain core programs ( § 7.1) will target about ∼ 10 4 . 5 previously known quasars with multiple additional optical spectral epochs. SDSS-V will also provide optical counterpart spectra for ∼ 10 5 . 5 Xray sources ( § 7.2), especially recently-discovered X-ray sources from SRG/eROSITA (Predehl et al. 2021).  \nIn DR18, BHM is releasing two categories of data: i) initial catalogs of candidate targets for its main science programs, which may provide guidance to the community in planning for future SDSS-V data releases, and ii) optical BOSS spectra for ∼ 10 4 candidate counterparts to eROSITA X-ray sources from the eROSITA Final Equatorial Depth Survey field (eFEDS, § 7.3; Brunner et al. 2022). In the subsections below, we provide a high-level summary of those BHM science programs that directly flow down from the driving science goals of the project (i.e., the 'core' programs); these are summarized in Table 4. Further details of the target selection criteria for the full set of BHM target cartons released in DR18 can be found in Appendix B and on the SDSS DR18 website 11 . As in the MWM section above, these targeting selections provide input into the observational design software ( § 10). The actual targets that are finally observed are a subset of these selections, determined by the survey optimization software.", '7.1. Spectral time-domain programs': 'The time-domain BHM core programs will target about ∼ 10 4 . 5 previously known quasars with multiple additional optical spectral epochs. These spectral time-domain programs aim to sample a broad range of timescales and cadences, ranging from days to decades (when all SDSS data are combined), as different aspects of quasar physics result in variability on very different time scales. SDSS-V studies black hole masses via reverberation mapping, possible SMBH binarity, timeresolved accretion events, broad line region (BLR) dynamics, and Broad Absorption Line Quasi-Stellar Object (BALQSO) outflows. The SDSS-V quasar timedomain programs build on the results and experience of earlier generations of SDSS, e.g., the SDSS-III/IV rever-  \nTable 3. Milky Way Mapper Cartons  \nNote -  \nberation mapping project (RM; Shen et al. 2015) and the Time Domain Spectroscopic Survey (TDSS; MacLeod et al. 2018), to enable long time baselines.', '7.1.1. All-Quasar Multi-Epoch Spectroscopy': 'The All-Quasar Multi-Epoch Spectroscopy (AQMES) program is core to the BHM science, with different tiers in survey area and number of epochs. It includes cartons that are aimed at wide areas and low cadence, and cartons aimed at a more modest area with higher cadence (see Table 4). Together these two tiers add new epochs in SDSS-V for ∼ 22,000 quasars that already have at least one previous epoch of spectroscopy from SDSSI-IV. These AQMES targets are selected from the SDSS DR16 quasar catalog (Lyke et al. 2020) and are readily observable from the Apache Point Observatory.  \nFor ∼ 20,000 known quasars, the primary associated targeting carton is bhm aqmes wide2 . This carton aims to add ∼ 2 additional epochs of SDSS-V optical spectroscopy for each of these known SDSS quasars. When combined with their archival SDSS optical spectra these data will sample ∼ 1-25 yr timescales (observer frame). The primary science goals include probing the BLR dynamics of the most massive black holes, constraining the statistics of changing look quasars, and charting broad absorption line (BAL) disappearance/emergence. This is a relatively wide area, but low-cadence time-domain tier, encompassing ∼ 2000-3000 deg 2 of the sky.  \nFor ∼ 2000 quasars, the bhm aqmes medium carton (Table 4) aims to add ∼ 10 optical spectral epochs in SDSSV, probing down to 1-month to 1-year timescales (in addition to the longer baseline timescales enabled with archival SDSS spectroscopy). The primary science goals of AQMES-Medium are to trace out BLR structural and dynamical changes, including BLR changes in modest mass SHMBs. This is a medium time-domain tier in area and cadence, encompassing ∼ 200-300 deg 2 .', '7.1.2. Reverberation Mapping': 'The Reverberation Mapping (RM) program is core to the BHM science of measuring black hole masses.  \nFor ∼ 1000 quasars in 4-5 dedicated fields to be targeted under the BHM RM program, a set of cartons (with names starting with bhm rm , Table 4) aim to obtain optical repeat spectra with a high cadence of up to ∼ 174 epochs, which sample down to (observer frame) timescales of days to weeks. The time lags between the continuum and BLR emission, plus line velocity widths, yield virial estimates of the black hole mass, advancing RM measures yet further to a broad range of luminosity and redshift. This is a small-area but high-cadence time-domain tier, encompassing a total of ∼ 30 deg 2 .', '7.2. Spectroscopic follow-up of X-ray sources': 'In addition to the time-domain science projects described above, BHM is carrying out a program of spectroscopic characterization of counterparts to an unprecedentedly large sample of X-ray sources. In almost all cases this will be via optical spectroscopy. The broad science emphasis is to chart the astrophysics, and the growth and evolution, of SMBHs. The X-ray selection provides a probe of accretion onto SMBHs that is significantly less sensitive to intervening absorption, and that generally selects a broader range of AGN luminosities, than purely optical-based selections. BHM features a large core program aimed at eROSITA X-ray sources ( § 7.2.1) and a substantial complementary program following up Chandra archival X-ray source catalogs ( § 7.2.2).', '7.2.1. Spectroscopic Identification of eROSITA Sources': "The SPectroscopic Identification of ERosita Sources (SPIDERS) program is core to BHM science and will help reveal the connections between statistical samples of X-ray emitting quasars/AGN and clusters of galaxies, and the large mass structures that they trace. The BHM SPIDERS program expands greatly on the SDSSIV SPIDERS program (e.g., Clerc et al. 2016; Dwelly et al. 2017; Comparat et al. 2020).  \nThe main goal of the SPIDERS program (sometimes referred to as the '(Southern) Hemisphere' survey) is to provide complete and homogeneous optical spectroscopic follow-up of ∼ 10 5 . 5 X-ray sources detected by eROSITA, across ∼ 10,000 deg 2 at high Galactic latitude (nominally | b | > 15 deg), within the German or 'DE' half of the sky. Ultimately, SPIDERS, via its wide-area survey, aims to obtain the optical spectroscopic identifications and redshifts, evolution, and astrophysics of ∼ 250,000 counterparts to X-ray point-like sources. It is anticipated that AGN/quasar identifications will form the large majority of the targets, but with a significant minority of X-ray emitting stars (from compact binaries to coronal emitters). Eventually, SPIDERS will use X-ray sources from eROSITA's first 1.5 years of survey operation (termed 'eRASS:3' because it contains data from three passes over the whole sky), which were completed in June 2021. The SPIDERS 'AGN' project cartons have names that start with bhm spiders agn (Table 4). However, note that the initial SPIDERS targeting information in v0.5.3 released in DR18 is derived from the somewhat shallower first 6 months of eROSITA-DE observations ('eRASS:1').  \nAn additional SPIDERS project is targeting ∼ 10 4 Xray emitting clusters of galaxies ( > 5 × 10 4 galaxy targets), selected from a combination of X-ray imaging and  \nthe eROSITA red-sequence Matched-filter Probabilistic Percolation galaxy cluster finding algorithm (eROMaPPeR; Rykoff et al. 2014; Ider Chitham et al. 2020) applied to multi-band wide+deep optical/IR imaging catalogs. For the SPIDERS clusters cartons (with names including bhm spiders clusters ), the new SDSS-V spectroscopy will provide redshifts and confirmations for the candidate clusters, as well as constraints on the velocity dispersion of the member galaxies. See Bulbul et al. (2022) for additional discussion on the complexity of selecting galaxy clusters in X-ray data sets.  \nA related pilot survey that began in SDSS-IV, and extended into early SDSS-V, has already largely completed BOSS spectroscopy for ∼ 10 4 candidate counterparts in the eROSITA-eFEDS mini-survey field, a ∼ 140 deg 2 region of the sky. The optical spectra in eFEDS are a centerpiece of the DR18 data release, and are detailed further in § 9.1.", '7.2.2. Chandra Source Catalog': 'The Chandra Source Catalog (CSC) program is a more modest, complementary program of mainly optical spectroscopy of X-ray counterparts (but including some IR APOGEE spectra as well). The SDSS-V/CSC program produces identifications, redshifts, and other properties of tens of thousands of X-ray source counterparts selected from the Chandra Source Catalog 12 (Evans et al. 2010); again many are likely to be verified as AGN in their SDSS-V spectra. The CSC sample is expected to probe fainter X-ray fluxes than the SPIDERS Hemisphere samples. The CSC target cartons released as part of DR18 are based on CSC2.0. In the future we plan to switch to the more recent CSC2.1 catalog in order to increase the available pool of targets.', '7.3. The SDSS-V/eFEDS Mini-survey': "The SDSS-V/eFEDS survey is a pathfinder component of the BHM survey program that exploits early performance validation observations from the SRG/eROSITA X-ray telescope in the eFEDS field (Brunner et al. 2022). The eFEDS X-ray footprint comprises 140 deg 2 centered near ( α, δ ) = (9 h , +1 · ), encapsulating the 'GAMA09' Field (Driver et al. 2009). We used plate observations at APO to collect optical BOSS spectroscopy for counterparts to both point-like and extended X-ray sources (Salvato et al. 2022; Klein et al. 2022). From past experience (e.g., Menzel et al. 2016; LaMassa et al. 2019; Clerc et al. 2016, 2020), one can  \nexpect these X-ray populations to be numerically dominated by AGN and clusters of galaxies, but we also expect a substantial minority to be associated with stellar coronal emitters or accreting compact objects.  \nBelow we give a summary of the observational goals, target selection, and survey strategy for the SDSSV/eFEDS observations. Details of the plate design and the scope and quality of the observed dataset can be found in § 9.1.", '7.3.1. SDSS-V/eFEDS Observational goals': 'The primary observational goal for this program was to achieve near-complete and reliable redshifts and classifications for optical counterparts to X-ray sources that were detected as part of the eROSITA/eFEDS performance verification survey, particularly for counterparts in the magnitude range 16 < r < 22 AB. On one hand, this goal was constrained by the number of hours of dark observing time available to the project, a general desire to minimize the total number of drilled plug plates, and the overall capabilities of the plate system to place fibers on naturally clustered targets. On the other hand, this goal of high completeness was assisted by the wealth of previous spectroscopic survey data in the eFEDS field, both from previous SDSS generations and from other telescopes and instruments. Our strategy was therefore to prioritize targets that did not have existing high quality spectroscopic observations.', '7.3.2. Target selection for SDSS-V/eFEDS plates': "The generation of targeting used for the eFEDS plates, during the Dec 2020-May 2021 run of plate operations predates the global v0.5.3 targeting information that is being released in DR18. The parent catalogs from which the eFEDS targets were selected were derived from early reductions of the eROSITA/eFEDS X-ray dataset, and are based on early attempts to match those Xray sources to longer-wavelength counterparts provided by several supporting optical/IR catalogs, including the DESI Legacy Survey (DR8; Dey et al. 2019), SDSS DR13 (Albareti et al. 2017), and the Hyper SuprimeCam Subaru Strategic Project (HSC-SSP DR2; Aihara et al. 2019). The eFEDS science target selection process concentrates on AGN candidates (one target carton) and galaxy cluster candidates (four cartons):  \nbhm spiders agn-efeds : A carton that contains candidate AGN targets found in the eROSITA/eFEDS X-ray survey field. This carton provides optical counterparts to point-like (unresolved) X-ray sources detected in early reductions (eROSITA Science Analysis Software, eSASS, version 'c940/V2T') of the eROSITA performance  \nTable 4. Black Hole Mapper Core Cartons 1  \nNote -  \nvalidation survey data in the eFEDS field. The sample is expected to contain a mixture of QSOs, AGN, stars and compact objects. The X-ray sources have been cross-matched by the eROSITADE team to the Legacy Survey 13 optical/IR counterparts (Salvato et al. 2022).  \nbhm spiders clusters-efeds-ls-redmapper : A carton that contains galaxy cluster targets found in the eROSITA/eFEDS X-ray survey field. The carton provides a list of galaxies that are candidate members of clusters selected from early reductions (eSASS version 'c940') of the eROSITA performance verification survey data. The parent sample of galaxy clusters and their member galaxies have been selected via a joint analysis of X-ray and (multiple) optical/IR datasets using the eROMaPPeR red-sequence finder algorithm (Rykoff et al. 2014; Ider Chitham et al. 2020). This particular carton relies on optical/IR data from the DESI Legacy Surveys (Dey et al. 2019).", 'bhm spiders clusters-efeds-sdss-redmapper :': 'Similar to the bhm spiders clusters-efeds-lsredmapper carton, except that the red sequence finder algorithm is run on the SDSS DR13 photometric catalogue (Albareti et al. 2017).', 'bhm spiders clusters-efeds-hsc-redmapper :': 'Similar to the bhm spiders clusters-efeds-lsredmapper carton, except that the red sequence finder algorithm is run on the HSC-SSP DR2 photometric catalogue (Aihara et al. 2019).  \nbhm spiders clusters-efeds-erosita : This carton includes manually-identified counterparts to Xray extended sources that were not also selected by the eROMaPPeR algorithm, when applied to any of the DESI Legacy Survey, SDSS-DR13, or HSC-SSP datasets.  \nAdditional details on these cartons can be found in Appendix B and at https://www.sdss.org/dr18/bhm/ programs/cartons/.', '8. MOS OPEN-FIBER PROGRAMS': "The hardware and the survey strategy for SDSS-V's MOS programs were designed around a set of core science cases that define this part of the survey. The underlying target densities in these science cartons vary dramatically across the sky, from star-rich Baade's Window towards the Galactic bulge to sparse high galactic latitudes. In addition, the FPS is subject to geometric constraints in placing fibers within a pointing's field of view: in a given individual exposure, fibers cannot be placed closer than ∼ 50 '' to each other, and given the limited patrol radius of each robot - the mean fiber density across the field of view cannot be  \nchanged. These constraints imply that after survey optimization for SDSS-V's core science, many robots with either BOSS or APOGEE fibers remain unallocated. After simulating the entire survey, over three million anticipated fiber-exposures remained available.  \nIn light of this, SDSS-V set up an 'open fiber' program, based on multiple collaboration-wide calls for ideas and proposals, that serves three purposes. First, and most immediately, to make sure that as few fibers as possible go scientifically unused. Second, to provide a mechanism to broaden the science case beyond the initial, defining science cases. And third, to provide a mechanism, through repeated open fiber proposal calls, to incorporate scientifically exciting targets that only become known or available as the survey goes on.  \nIn 2020, SDSS-V issued a first call for open fiber proposals from the consortium, whose results have entered the targeting documented here in various ways. Boundary conditions for these proposals were that i) the science goals could be reached with single 15 minute exposures using either APOGEE or BOSS; ii) the targeting information was freely available to all consortium members, and a target selection function could be specified; iii) the existing core science goals were complemented or enhanced; and iv) the science goals had proponents within the SDSS-V consortium.  \nThe project received nearly 30 proposals in late 2020. Much of the proposed science fell into one of three broad categories: 1) more extensive surveying of AGNs and Xray sources across the sky; 2) broader stellar physics, in particular binary star physics, across the CMD; and 3) studying the Milky Way's stellar halo and metal-poor population, which (intentionally) had not been a focus of the MWM Galactic Genesis program ( § 6). These programs were reviewed in early 2021 by the SDSS-V technical advisory group and the project leadership, who called on three consortium members not involved in the proposals to help with the review. The resulting target cartons are listed in Table 5. For the v0.5.X versions of the targeting, including the v0.5.3 generation released in DR18, we adopted these cartons as-is. In future versions of the target selection, a number of these cartons may be consolidated and incorporated into the versioned science programs of the BHM and MWM surveys.", '9. SPECTRA': 'This section describes the spectra being released in DR18, particularly the eFEDS survey and its data products.', '9.1. The SDSS-V/eFEDS mini-survey': 'The scientific objectives and carton design of the eFEDS program can be found in § 7.3. Below we describe the observational design details and the final data set.', '9.1.1. Tiling and plate design': 'Due to COVID-19-induced delays in the completion of the FPS systems, SDSS-V started observations at APOusing the existing fiber plugplate system, including the eFEDS observations. Modifications to the existing system included a new joint BOSS+APOGEE configuration, in which the focal plane was populated with 500 fibers feeding a BOSS optical spectrograph and 300 fibers feeding an APOGEE IR spectrograph. New procedures and software were put in place to manage target selection, fiber assignment and plate design for the single season of SDSS-V data that were obtained in this mode. These procedures will be described in more detail in a future publication (Covey et al. in prep). Here we provide a summary of special considerations that apply specifically to the SDSS-V/eFEDS plates.  \nEach plate-based observing run comprises a set of plates created to observe a set of targets from a given field (a region of the sky) and drilled to observe around a specific hour angle (to account for atmospheric refraction effects). The targets on a given plate were assigned using a specific combination of cartons ( § 7.3.2). For each plate, we created a prioritized list of cartons (including cartons associated with calibration targets such as skies and spectrophotometric standards, § 5.2) to fill the fibers for each spectrograph. Individual fiber filling rules were shared by multiple plates in the same observing run or even across different runs; different fiber filling rules are distinguished by shifting in priority of a carton with respect to another, or an update on the version of the carton that was used. Each combination of fiber filling rule and unique set of targets was identified with a designID . Figure 5 shows the sky locations of the SDSS-V/eFEDS sources in relation to the other data sets available in the region.  \nSDSS-V/eFEDS plates were designed within two independent iterations of the tiling and plate design process. The first of these plate runs ( 2020.11.a.bhm-mwm ) consisted of 31 initial plates spanning most of the ∼ 140 deg 2 eFEDS field, with an inner region (roughly corresponding to the GAMA09 field) targeted with two plates per sky position. The large fractional overlap between the eFEDS plates required special attention to ensure proper control over which targets were prioritized in which plates, as the standard SDSS platedesign software treats all plates independently. This complexity, and constraints on the fiber reach of the plate fibers, re-  \nTable 5. Open Fiber Cartons  \nsulted in only 20 of the 2020.11.a.bhm-mwm plates being available for observation. A second eFEDS plate run ( 2021.01.a.bhm-mwm ) was designed to recover eFEDS targets from the unobservable plate designs and to take advantage of updated projections of the available observing time and plug-plate manufacturing resources. A new heuristic tiling algorithm resulted in all 17 plates from this run being observed.  \nFor each of these 37 SDSS-V/eFEDS plates, we reserved at least 80 BOSS fibers per plate for skies and 20 BOSS fibers for spectrophotometric standard stars, leaving up to 400 BOSS fibers for science targets 14 . We applied a bright limit for science targets of g psf , r psf , i psf > 16 . 5 AB, and we avoided placing fibers near brighter stars. These bright limits are imposed to allow observation of the faint end of the target population (Figure 6) without significant degradation from on-chip cross-talk between neighbouring BOSS fiber traces.', '9.1.2. Spectroscopic observations, reductions, and data quality': "The SDSS-V/eFEDS observing strategy prioritized coverage over depth, given the somewhat uncertain amount of good quality observing time that would be available whilst the eFEDS field was visible from APO. By the end of the visibility window (Dec 2020-May 2021), all 37 eFEDS plates had achieved a total fiducial g -band signal-to-noise ratio squared (SNR 2 g ) of at least 7.5. However, most of the plates are significantly deeper than that, with 33/37 of the eFEDS plates having SNR 2 g > 10 (comparable to the typical exposure depth in BOSS/eBOSS; Dawson et al. 2016), and more than half the plates having SNR 2 g > 20. The fiducial SNR 2 in the i -band is typically twice that measured in the g -band. An updated version of the BOSS idlspec2d data reduction pipeline (Bolton et al. 2012, see § 10.1 for updates) was used to generate a set of spectral data products per PLATE-MJD combination, with individual 1D spectra for each combination of PLATE-MJD-CATALOGID .  \nMany science targets were observed on more than one PLATE-MJD combination. Therefore, a specialized coadding algorithm (within idlspec2d ) was additionally implemented for these eFEDS plates, collating spectroscopic data across plates and MJDs, in order to increase SNR in the 1D spectra ( § 10.1). This routine creates a single stacked spectrum per astrophysical object, using all suitable SDSS-V BOSS data. A total of 13269 specially coadded spectra from eFEDS science targets  \nare released in DR18, along with 2608 skies, 671 spectrophotometric standards, and several hundred unvetted spectra not intended for scientific use ( § 9.2).  \nRedshifts, classifications, and quality flags were computed automatically on the specially coadded spectra using the spec1d template fitting pipeline (Bolton et al. 2012). A warning flag was set for 669/13269 science spectra, indicating a problem with the data or the fit. Of the 12600 science spectra without warnings, the main pipeline gives source classifications of 'QSO' for 6204, 'GALAXY' for 4782 and 'STAR' for 1614 spectra. Pipeline redshifts for non-flagged 'QSO' and 'GALAXY' classified spectra span the range 0 . 0 < z < 4 . 5, with 90% of these objects falling in the range 0 . 14 < z < 2 . 55 (median 0.55).  \nFigure 6 shows the derived redshift distribution for good quality ( ZWARNING =0) spectra obtained from the SDSS-V/eFEDS plates, grouped by their primary target selection criteria. The observed redshift distributions are broadly in line with expectations. SPIDERS AGN targets span a wide range of redshifts (0 < z < 4 . 5, median 0.8), including a small fraction (10.0%) that are revealed by spectroscopy to be stellar in nature. SPIDERS galaxy cluster targets are found at relatively lower redshift (0 . 1 < z < 0 . 6, median 0.28).  \nIn order to increase the completeness and reliability of the redshifts and classifications derived from these spectra, we carried out visual inspections of a large fraction of the SDSS-V/eFEDS spectra. Those inspections have been combined with earlier SDSS spectroscopic redshift information and with non-SDSS redshift information gathered from the literature. Please see Merloni et al., (in prep.), and the associated Value Added Catalog 15 ( § 11.2) for further details of the eFEDS spectroscopic compilation.  \nThis data set has enabled in-depth study of the clustering of X-ray selected AGN, resulting in new constraints on the AGN halo occupation distribution (Comparat et al. 2023).", '9.1.3. Accessing eFEDS Data': "To download the eFEDS spectra, go to https://dr18. sdss.org/sas/dr18/spectro/boss/redux/eFEDS/; the associated data models are at https://data.sdss.org/ datamodel/files/BOSS SPECTRO REDUX/RUN2D/ and subdirectories. Note that these spectra were generated using the specialized co-adding scheme described in § 9.1.2. The 'standard' coadds can be found at https: //dr18.sdss.org/sas/dr18/spectro/boss/redux/v6 0 4/. To download the eFEDS VAC of improved redshifts  \nFigure 5. SDSS spectroscopic coverage in the eFEDS field ( § 9.1), color-coded by the SDSS phase when the spectrum was taken. Green points show the locations of individual SDSS/BOSS spectra made available in DR16 or before; orange corresponds to SDSS-IV/eFEDS BOSS spectroscopy released in DR17, and blue shows the new optical BOSS spectroscopy being released in DR18. X-ray-selected galaxy clusters, specifically targeted in DR17 and DR18, are readily visible as compact concentrations of points. The approximate bound of the eROSITA X-ray data is shown with the thick black line. The southwest (lower right) corner is empty of DR16 spectroscopy because it lies outside the nominal SDSS imaging footprint. The map is shown on a tangential projection, in Equatorial coordinates, with units of degrees.  \n<!-- image -->  \n( § 11.2), visit the DR18 VAC website: https://www. sdss.org/dr18/data access/value-added-catalogs/.", '9.2. Other Spectra': 'Users of DR18 may come across science spectra (i.e., not standard stars or sky targets) that were included in the eFEDS plates ( § 9.1) but that are not associated with eROSITA/eFEDS target cartons. These data are included in DR18 for logistical reasons but are not intended for scientific exploitation (e.g., they have not undergone any quality assurance testing). They can be identified by one of the following FirstCarton labels in the database:  \n- · mwm cb cvcandidates\n- · mwm cb gaiagalex\n- · mwm cb uvex1\n- · mwm cb uvex2\n- · mwm cb uvex3\n- · mwm cb uvex4\n- · mwm cb uvex5\n- · mwm halo bb\n- · mwm halo sm\n- · mwm snc 100pc', '· mwm wd': 'Users can expect improved and vetted versions of these spectra in DR19.', '10. SOFTWARE': 'SDSS operations, data processing, and analysis rely on a large suite of software components. A limited number of these, new or updated for SDSS-V, have already been released or are being released as part of DR18.', '10.1. Updates to the BOSS Spectral Reduction Algorithms': "The optical BOSS data released in DR18 ( § 9.1) are processed with version v6 0 4 of the BOSS pipeline software idlspec2d (Bolton et al. 2012; Dawson et al. 2013, Morrison et al. in prep). This is the first official version of idlspec2d to be used for SDSS-V, with a few changes since the last full public release ( v5 13 2 ) of SDSS-IV/eBOSS. All SDSS-V versions of idlspec2d are available for download from the SDSS GitHub, with the version described here available at https://github. com/sdss/idlspec2d/releases/tag/v6 0 4.  \nOne of the most significant operational changes to the pipeline is a modification to reduce 500 fibers from a sin-  \nFigure 6. Upper panel: Optical magnitude distribution of BOSS science targets in the SDSS-V/eFEDS plates ( § 9.1). Note that target magnitudes in SDSS-V are synthesized from a range of input photometric systems; in this case we show the equivalent of an r -band 'fiber2mag' (i.e., the light falling into a 2 arcsec diameter fiber under nominal APO seeing conditions). Lower panel: Distribution of pipeline-determined redshifts for science targets in the SDSS-V/eFEDS plate reductions ( § 9.1.2). Spectra with redshift fitting warnings have been removed. Redshifts outside the range of the plots are included in the extremal bins. Target selection for SPIDERS AGN and Clusters is described in § 7.3.2, and for other targets in § 9.2.  \n<!-- image -->  \ngle BOSS spectrograph, rather then a combined reduction of 1000 fibers from the twin BOSS spectrographs. This change was made to support the move of the second BOSS spectrograph to LCO.  \nA number of smaller changes were implemented into the pipeline to both improve ongoing reductions and facilitate future reductions of FPS/BOSS data. First, to improve the radial velocity precision of the extracted spectra, a refined arc lamp linelist (developed for the SDSS-IV MANGA project; Bundy et al. 2015) replaced the list from SDSS-IV, and skylines are utilized as a second-level calibrator. This second step required an adjustment to the outlier exclusion algorithm (designed to exclude cosmic rays) to preserve the peaks of the skylines by increasing the outlier rejection from 4 σ to 50 σ .  \nThis change, in some rare cases, might leave the remnant of a cosmic ray in the extracted spectra.  \nSecond, we modified the coadding scheme of targets between exposure frames and the red/blue cameras; individual spectra are now grouped according to the RA,Dec coordinates of the fiber(s) (or the SDSS-V CatalogID, if one exists), rather than on the combination of BOSS PLATE-MJD-FIBERID . The coadding scheme was also split into a two step process, in which the red and blue data for each exposure are combined, and then the all-exposures red and blue data are combined to produce coadds for the full observation epoch. These changes were implemented to improve the signal-to-noise ratio of the final reduced spectra.  \nThird, v6 0 4 was modified to produce a special version of the DR18 SDSS-V/eFEDS spectra ( § 9.1.2), in addition to the existing standard pipeline results. This new combination includes every exposure of each target, regardless of the plate on which it was observed, to produce a set of spectra with maximum signal-to-noise. Both the standard pipeline, v6 0 4 , and the eFEDS special coadds are available through the SAS 16 ; and the CAS using SkyServer 17 . Future data releases will include variations of this special coadding routine, with the spectra included in each coadd chosen to fulfil the science requirements of the individual SDSS-V science programs.  \nFourth, in addition to the changes in the reduction and coadding schemes, some modifications were made to the spec1d analysis part of idlspec2d . Utilizing 849 SDSS-IV RM quasars (Shen et al. 2019) and the Weighted empca package (Bailey 2012, 2016), a new set of QSO PCA templates are used for PCA reconstruction and redshift estimation of SDSS-V quasars. These new PCAtemplates are implemented with 10 eigenvectors instead of the 4 used in SDSS-I through SDSS-IV. To further support the MWM targets on the reduced eFEDs plates, on the observed MWM plates (not released in DR18 but documented here for completeness), and in future FPS observations, the SFD model for dust extinction (Schlegel et al. 1998; Schlafly & Finkbeiner 2011) for MWM plates was replaced by the 3D Bayestar2015 dust map (Green et al. 2015) to properly account for differential dust extinction within the Milky Way. The package pyXCSAO (Kounkel 2022), a python replication of the xcsao package (Kurtz et al. 1992; Mink & Kurtz 1998; Tonry & Davis 1979), was added as part of the spec1d analysis pipeline for cross-correlating a spectrum  \nagainst template spectra of known velocities. While this step is run for all targets, the results are only valid for stellar targets.  \nFinally, idlspec2d 's internal Python dependencies were updated to Python3, with the deprecation of Python 2.7. All of changes described here improve either data quality or spectroscopic classification success rates, or support the changes to the BOSS spectrograph for the SDSS-V plate program and FPS observations.", '10.2. Migration to GitHub': 'For SDSS-V, all of the SDSS software has been moved to a GitHub Organization 18 , from the previous Subversion private repository. With the exception of a few repositories containing proprietary code or credentials, all the code is publicly available under a BSD 3-Clause license. This includes most of the operational software, telescope and instrument control software, and data reduction pipelines.', '10.3. MOS Software for DR19': "The migration from plug-plates to robotic fiber positioners in SDSS-V required the development of a suite of new software for targeting and operations. Although this software was not used for the acquisition of DR18's spectra ( § 9.1), it is currently in use for FPS operations and will become relevant for DR19 and future data releases. Here we provide a short summary of FPS targeting and operations as a preview for those data releases. Further details are given in S'anchez-Gallego et al. (2020).  \nCombining the complex set of observing constraints and epoch cadences defined by the various target selection cartons into a set to observable FPS configurations requires the use of an specialized algorithm. robostrategy is the pipeline that takes the outputs of target selection and determines how the targets should be observed. It determines the cadence with which each field will be observed, which includes the number of epochs, the number of observations ('designs') per epoch, and the desired observing conditions for each design (including, e.g., the sky brightness conditions and hour angle). At the beginning of each night of observations, the software roboscheduler selects the optimal list of designs to be observed based on cadence requirements and observing conditions, as well as on previous observations and achieved completion.  \nOne major challenge of the SDSS robotic fiber positioner system derives from the fact that the patrol radius of each positioner overlaps with its neighboring  \nones. For a given set of target-to-positioner assignments defined in a robostrategy design, an algorithm named Kaiju (Sayres et al. 2021) provides a deterministic trajectory for each robotic positioner from a starting 'folded' state, in which all robots are identically oriented, to the desired FPS configuration. Kaiju works following a reverse-solve method in which it is considered simpler to calculate collision-free trajectories for each robot from a complex, deployed state, to a latticelike folded configuration. To create a path between two observable configurations Kaiju calculates the reverse trajectories from each configuration to the folded state, and then applies the reverse trajectory. Following this approach Kaiju is able to determine deadlock-free trajectories between any two physically reachable robot configurations in over 99% of cases (Sayres et al. 2021).", '11. VALUE-ADDED CATALOGS': "In addition to its fundamental data products, SDSS regularly includes 'Value Added Catalogs' as part of its data releases 19 . These catalogs contain curated quantities from the data, usually to enable a specific scientific projects, but recognized as having value above and beyond the particular project for which the catalog was initially constructed.", '11.1. SDSS-IV VACs': "Table 6 includes the following VACs that rely on SDSS-IV data but are updated or published for the first time after DR17:  \nBACCHUS Analysis of Weak Lines in APOGEE Spectra (BAWLAS) : Weak-lined species in APOGEE spectra are challenging to measure and in some cases, cannot be done with the standard ASPCAP pipeline. This VAC contains approximately 120,000 high-SNR giants from APOGEE DR17, for which Na, P, S, V, Cu, Ce, and Nd abundances and 12 C/ 13 C isotopic ratios have been derived with a specialized analysis (Hayes et al. 2022). An updated version of the code BACCHUS (Brussels Automatic Code for Characterizing High accUracy Spectra; Masseron et al. 2016) was used in the derivation, along with ASPCAP fundamental stellar parameters but also a dedicated set of individual line quality flags and a new prescription for identifying upper limits. Hayes et al. (2022) show how these newly derived abundances compare with literature values and provide examples of scientific projects that can be done with APOGEE and the new catalog, ranging from nuclear  \nTable 6. New or Updated Value Added Catalogs  \nphysics to Galactic chemical evolution and Milky Way population studies.  \nMaNGA Dwarf Galaxy Sample (MaNDala): This VAC presents properties for a sample of 125 dwarf galaxies ( M ⋆ < 10 9 M ⊙ ) observed with MaNGA (Cano-D'ıaz et al. 2022), including newly derived photometric results, such as surface brightness, color, and position angle. Also measured are photometric profiles along with S'ersic fits and new estimations of effective radii for all of the galaxies, using DECaLS DR9 g, r, z images (Dey et al. 2019). Analysis of the MaNGA data provides estimates of M ⋆ , SFRs, metallicities, ages, and other properties, using MaNGA Pipe3D data products (S'anchez et al. 2016, 2018). Details for the MaNDala sample and analysis are given in Cano-D'ıaz et al. (2022).  \nMaNGA Visual Morphology : This is an update of a VAC, originally released in DR17 (Section 5.5.2 in Abdurro'uf et al. 2022), that contains visual morphological classifications for MaNGA galaxies based on SDSS and DECaLs (Dey et al. 2019) images. See V'azquez-Mata et al. (2022) for details.", '11.2. SDSS-V VACs': 'The only VAC in DR18 derived from SDSS-V data is that providing supplementary properties for the eFEDS spectroscopic data set ( § 7.3).  \nThis VAC provides updated redshift and classification information for optical counterparts to X-ray sources detected in the eFEDS field (Brunner et al. 2022; Salvato et al. 2022). We update the spectroscopic redshift and classifications (with respect to Salvato et al. 2022) using a large spectroscopic compilation dominated by SDSS optical spectroscopy. Most importantly, we include new information from the 37 dedicated SDSS-V/eFEDS plates, described in detail in § 9.1. We combine automated redshifts and classifications, derived from the BOSS idlspec1d pipeline ( § 10.1), with an extensive set of visual inspections, which together increase the reliability and completeness of the spectroscopic coverage.  \nThe VAC includes three separate catalogs:  \n- i) eFEDS Main speccomp - an update of redshift and classification information for the eFEDS Main (0.2-2.3 keV selection) source counterparts catalog;\n- ii) eFEDS Hard speccomp - an update of redshift and classification information for the eFEDS Hard band (2.3-5 keV selection) source counterparts catalog; and\n- iii) eFEDS SDSSV spec results - a catalog of spectroscopic redshifts and classifications derived solely from the SDSS-V/eFEDS plate data set, supplemented by the results of an extensive visual inspection process.  \nA full description of this VAC will be provided in Merloni et al. (in prep).', '12. SUMMARY AND DR19 PREVIEW': 'In this paper, we have described the contents of the first data release of SDSS-V, which is also the eighteenth data release of the SDSS family of surveys. DR18 contains extensive targeting information for the Milky Way Mapper ( § 6) and Black Hole Mapper ( § 7), both compiled target catalogs and the selection algorithms for their numerous scientific programs. Nearly ∼ 25,000 new spectra for X-ray sources in the eROSITA eFEDS field are also made available, along with substantial supplementary information, including improved redshift and classifications based on visual inspections. Significant improvements to the BOSS data spectral reduction pipelines were also made, in support of these and other optical spectra.  \nThe next SDSS-V data release will be DR19, anticipated in 2024. This will contain the first MWM spectra and derived stellar parameters & abundances, and the first spectra and derived properties from the primary BHM programs. Updates to the targeting catalogs presented in this paper will also be made available, along  \nwith updated simulations that predict the number of candidate targets in a carton that are likely be to observed. Additional tools for accessing and exploring all of the data are also anticipated to be released.  \nThe capabilities and flexibility of SDSS-V make it unique among recent, ongoing, or imminent surveys, with well-vetted hardware, software, and collaboration infrastructure serving as the foundation for new innovations in all three areas. SDSS-V looks forward to expanding the SDSS legacy with high-quality, optical IFU data of 1000 deg 2 and optical + infrared spectra of millions of sources across the entire sky.', 'ACKNOWLEDGEMENTS': "The documentation workshop for DR18 ('DocuLlama') was held virtually in September 2022, organized by Anne-Marie Weijmans and Gail Zasowski. This event was the main venue for the documentation of DR18, including significant progress on this paper and the website, and was attended by Scott Anderson, Joel Brownstein, Joleen Carlberg, Niall Deacon, Nathan De Lee, John Donor, Tom Dwelly, Keith Hawkins, Jennifer Johnson, Sean Morrison, Jordan Raddick, Jos'e S'anchezGallego, Diogo Souto, Taylor Spoo, Ani Thakar, Nick Troup, Anne-Marie Weijmans, Gail Zasowski, William Zhang, three llamas, and an elderly goat named Nibblets.  \nFunding for the Sloan Digital Sky Survey V has been provided by the Alfred P. Sloan Foundation, the Heising-Simons Foundation, the National Science Foundation, and the Participating Institutions. SDSS acknowledges support and resources from the Center for High-Performance Computing at the University of Utah. The SDSS web site is www.sdss.org.  \nSDSS is managed by the Astrophysical Research Consortium for the Participating Institutions of the SDSS Collaboration, including the Carnegie Institution for Science, Chilean National Time Allocation Committee (CNTAC) ratified researchers, the Gotham Participation Group, Harvard University, The Johns Hopkins University, L'Ecole polytechnique f'ed'erale de Lausanne (EPFL), Leibniz-Institut fur Astrophysik Potsdam (AIP), Max-Planck-Institut fur Astronomie (MPIA Heidelberg), Max-Planck-Institut fur Extraterrestrische Physik (MPE), Nanjing University, National Astronomical Observatories of China (NAOC), New Mexico State University, The Ohio State University, Pennsylvania State University, Smithsonian Astrophysical Observatory, Space Telescope Science Institute (STScI), the Stellar Astrophysics Participation Group, Universidad Nacional Aut'onoma de M'exico, University of Arizona, University of Colorado Boulder, University of Illinois at  \nUrbana-Champaign, University of Toronto, University of Utah, University of Virginia, and Yale University.  \nThe Pan-STARRS1 Surveys (PS1) and the PS1 public science archive have been made possible through contributions by the Institute for Astronomy, the University of Hawaii, the Pan-STARRS Project Office, the MaxPlanck Society and its participating institutes, the Max Planck Institute for Astronomy, Heidelberg and the Max Planck Institute for Extraterrestrial Physics, Garching, The Johns Hopkins University, Durham University, the University of Edinburgh, the Queen's University Belfast, the Harvard-Smithsonian Center for Astrophysics, the Las Cumbres Observatory Global Telescope Network Incorporated, the National Central University of Taiwan, the Space Telescope Science Institute, the National Aeronautics and Space Administration under Grant No. NNX08AR22G issued through the Planetary Science Division of the NASA Science Mission Directorate, the National Science Foundation Grant No. AST-1238877, the University of Maryland, Eotvos Lorand University (ELTE), the Los Alamos National Laboratory, and the Gordon and Betty Moore Foundation.  \nThis publication makes use of data products from the Two Micron All Sky Survey, which is a joint project of the University of Massachusetts and the Infrared Processing and Analysis Center/California Institute of Technology, funded by the National Aeronautics and Space Administration and the National Science Foundation.  \nThis work is based in part on observations made with the Spitzer Space Telescope, which was operated by the Jet Propulsion Laboratory, California Institute of Technology under a contract with NASA.  \nThis publication makes use of data products from the Wide-field Infrared Survey Explorer, which is a joint project of the University of California, Los Angeles, and the Jet Propulsion Laboratory/California Institute of Technology, funded by the National Aeronautics and Space Administration.  \nThis work presents results from the European Space Agency (ESA) space mission Gaia. Gaia data are being processed by the Gaia Data Processing and Analysis Consortium (DPAC). Funding for the DPAC is provided by national institutions, in particular the institutions participating in the Gaia MultiLateral Agreement (MLA). The Gaia mission website is https:// www.cosmos.esa.int/gaia. The Gaia archive website is https://archives.esac.esa.int/gaia.  \nThe Legacy Surveys consist of three individual and complementary projects: the Dark Energy Camera Legacy Survey (DECaLS; Proposal ID #2014B-0404; PIs: David Schlegel and Arjun Dey), the Beijing-  \nArizona Sky Survey (BASS; NOAO Prop. ID #2015A0801; PIs: Zhou Xu and Xiaohui Fan), and the Mayall z-band Legacy Survey (MzLS; Prop. ID #2016A-0453; PI: Arjun Dey). DECaLS, BASS and MzLS together include data obtained, respectively, at the Blanco telescope, Cerro Tololo Inter-American Observatory, NSF's NOIRLab; the Bok telescope, Steward Observatory, University of Arizona; and the Mayall telescope, Kitt Peak National Observatory, NOIRLab. Pipeline processing and analyses of the data were supported by NOIRLab and the Lawrence Berkeley National Laboratory (LBNL). The Legacy Surveys project is honored to be permitted to conduct astronomical research on Iolkam Du'ag (Kitt Peak), a mountain with particular significance to the Tohono O'odham Nation.  \nNOIRLab is operated by the Association of Universities for Research in Astronomy (AURA) under a cooperative agreement with the National Science Foundation. LBNL is managed by the Regents of the University of California under contract to the U.S. Department of Energy.  \nThis project used data obtained with the Dark Energy Camera (DECam), which was constructed by the Dark Energy Survey (DES) collaboration. Funding for the DES Projects has been provided by the U.S. Department of Energy, the U.S. National Science Foundation, the Ministry of Science and Education of Spain, the Science and Technology Facilities Council of the United Kingdom, the Higher Education Funding Council for England, the National Center for Supercomputing Applications at the University of Illinois at UrbanaChampaign, the Kavli Institute of Cosmological Physics at the University of Chicago, Center for Cosmology and Astro-Particle Physics at the Ohio State University, the Mitchell Institute for Fundamental Physics and Astronomy at Texas A&M University, Financiadora de Estudos e Projetos, Fundacao Carlos Chagas Filho de Amparo, Financiadora de Estudos e Projetos, Fundacao Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio de Janeiro, Conselho Nacional de Desenvolvimento Cientifico e Tecnologico and the Ministerio da Ciencia, Tecnologia e Inovacao, the Deutsche Forschungsgemeinschaft and the Collaborating Institutions in the Dark Energy Survey. The Collaborating Institutions are Argonne National Laboratory, the University of California at Santa Cruz, the University of Cambridge, Centro de Investigaciones Energeticas, Medioambientales y Tecnologicas-Madrid, the University of Chicago, University College London, the DESBrazil Consortium, the University of Edinburgh, the Eidgenossische Technische Hochschule (ETH) Zurich, Fermi National Accelerator Laboratory, the University  \nof Illinois at Urbana-Champaign, the Institut de Ciencies de l'Espai (IEEC/CSIC), the Institut de Fisica d'Altes Energies, Lawrence Berkeley National Laboratory, the Ludwig Maximilians Universitat Munchen and the associated Excellence Cluster Universe, the University of Michigan, NSF's NOIRLab, the University of Nottingham, the Ohio State University, the University of Pennsylvania, the University of Portsmouth, SLAC National Accelerator Laboratory, Stanford University, the University of Sussex, and Texas A&M University.  \nBASS is a key project of the Telescope Access Program (TAP), which has been funded by the National Astronomical Observatories of China, the Chinese Academy of Sciences (the Strategic Priority Research Program 'The Emergence of Cosmological Structures' Grant #XDB09000000), and the Special Fund for Astronomy from the Ministry of Finance. The BASS is also supported by the External Cooperation Program of Chinese Academy of Sciences (Grant #114A11KYSB20160057), and Chinese National Natural Science Foundation (Grant #12120101003, #11433005).  \nThe Legacy Survey team makes use of data products from the Near-Earth Object Wide-field Infrared Survey Explorer (NEOWISE), which is a project of the Jet Propulsion Laboratory/California Institute of Technology. NEOWISE is funded by the National Aeronautics and Space Administration.  \nThe Legacy Surveys imaging of the DESI footprint is supported by the Director, Office of Science, Office of High Energy Physics of the U.S. Department of Energy under Contract No. DE-AC02-05CH1123, by the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility under the same contract; and by the U.S. National Science Foundation, Division of Astronomical Sciences under Contract No. AST-0950945 to NOAO.  \nThe national facility capability for SkyMapper has been funded through ARC LIEF grant LE130100104 from the Australian Research Council, awarded to the University of Sydney, the Australian National University, Swinburne University of Technology, the University of Queensland, the University of Western Australia, the University of Melbourne, Curtin University of Technology, Monash University and the Australian Astronomical Observatory. SkyMapper is owned and operated by The Australian National University's Research School of Astronomy and Astrophysics. The survey data were processed and provided by the SkyMapper Team at ANU. The SkyMapper node of the All-Sky Virtual Observatory (ASVO) is hosted at the National Computational Infrastructure (NCI). Development and support  \nof the SkyMapper node of the ASVO has been funded in part by Astronomy Australia Limited (AAL) and the Australian Government through the Commonwealth's Education Investment Fund (EIF) and National Collaborative Research Infrastructure Strategy (NCRIS), particularly the National eResearch Collaboration Tools and Resources (NeCTAR) and the Australian National Data Service Projects (ANDS).  \nThis paper includes data collected by the TESS mission. Funding for the TESS mission is provided by the NASA's Science Mission Directorate.  \nWe acknowledge the use of public data from the Swift data archive.  \nBased on observations obtained with XMM-Newton, an ESA science mission with instruments and contributions directly funded by ESA Member States and NASA. This research has made use of NASA's Astrophysics  \nData System Bibliographic Services.  \nFacilities: Du Pont (APOGEE), Sloan, Spitzer, WISE, 2MASS, Gaia, GALEX, PS1, TESS, Swift, CXO, XMM, eROSITA", 'REFERENCES': "Perruchot, S., Guy, J., Le Guillou, L., et al. 2018, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol. 10702, Ground-based and Airborne Instrumentation for Astronomy VII, ed. C. J. Evans, L. Simard, & H. Takami, 107027K, doi: 10.1117/12.2311996  \n- Pogge, R. W., Derwent, M. A., O'Brien, T. P., et al. 2020, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol. 11447, Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, 1144781, doi: 10.1117/12.2561113\n- Predehl, P., Andritschke, R., Arefiev, V., et al. 2021, A&A, 647, A1, doi: 10.1051/0004-6361/202039313\n- Price-Whelan, A. M., Hogg, D. W., Rix, H.-W., et al. 2020, ApJ, 895, 2, doi: 10.3847/1538-4357/ab8acc\n- Rix, H.-W., Hogg, D. W., Boubert, D., et al. 2021, AJ, 162, 142, doi: 10.3847/1538-3881/ac0c13\n- Rockosi, C. M., Lee, Y. S., Morrison, H. L., et al. 2022, ApJS, 259, 60, doi: 10.3847/1538-4365/ac5323\n- Rykoff, E. S., Rozo, E., Busha, M. T., et al. 2014, ApJ, 785, 104, doi: 10.1088/0004-637X/785/2/104\n- Salvato, M., Wolf, J., Dwelly, T., et al. 2022, A&A, 661, A3, doi: 10.1051/0004-6361/202141631  \nS'anchez, S. F., P'erez, E., S'anchez-Bl'azquez, P., et al. 2016,  \nRevMexAA, 52, 171. https://arxiv.org/abs/1602.01830  \nS'anchez, S. 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B., Horne, K., et al. 2019, ApJS, 241, 34, doi: 10.3847/1538-4365/ab074f", 'A. DETAILS OF MWM V0.5.3 TARGET CARTONS': "In this Appendix we provide the detailed criteria used to select the MWM target cartons that are being released as part of SDSS DR18. We remind the reader that inclusion in a carton means that the target fits the carton selection criteria, not that it is guaranteed to be observed.  \nFor each target carton, we provide the following information: The Description of selection criteria provides a short summary of the carton selection in human-readable terms. It also includes a list of the limits in color, magnitude, parallax, and other quantities applied to the carton's target candidates 20 . Data Sources gives the catalogs from which these quantities are drawn. In Target priority options , we indicate which priority is given to targets in this carton for observing; smaller priorities are more likely to be assigned fibers. The Cadence options describes which exposure time requirement(s) are assigned to sources in the carton. See Table 3 for each carton's instrument (BOSS or APOGEE) and the number of candidate targets that meet the carton's selection criteria.  \nA.1. manual mwm tess ob  \nDescription of selection criteria: A system selected from the Ijspeert et al. (2021) catalog of massive eclipsing binaries in TESS. Systems chosen were in the TESS Continuous Viewing Zones (CVZs) and had TESS lightcurves that show pronounced eclipses and intrinsic variability.  \nData Sources:  \nIjspeert et al. (2021)  \nTarget priority options:  \n2200  \nCadence options: bright 8x1, bright 8x2, bright 8x4", 'A.2. manual nsbh apogee': 'Description of selection criteria: List of targets drawn from public and private catalogs of binary systems with known or suspected black holes or neutron stars, such as X-ray binaries and pulsars. Must have a valid 2MASS H magnitude.  \nData Sources: 2MASS PSC (H), Gaia DR2 (G)  \nTarget priority options:  \n1400  \nCadence options: bright 1x1', 'A.3. manual nsbh boss': 'Description of selection criteria: List of targets drawn from public and private catalogs of binary systems with known or suspected black holes or neutron stars, such as X-ray binaries and pulsars. Must have a valid Gaia DR2 G magnitude.  \nData Sources: 2MASS PSC (H), Gaia DR2 (G)  \nTarget priority options:  \n1400  \nCadence options: bright 1x1, dark 1x2', 'A.4. mwm cb 300pc apogee': 'Description of selection criteria: Bright compact binary candidates within 300 pc.  \n- • ( FUV - 5 log 10 ( r est / 10)) > 14( FUV - NUV ) - 46\n- • r est < 300 pc\n- • H < 11  \nData Sources: Bailer-Jones et al. (2018) distance catalog ( r est ), 2MASS PSC (H), GALEX (FUV, NUV)  \nTarget priority options: 1400  \nCadence options: bright 1x1  \nA.5. mwm cb 300pc boss  \nDescription of selection criteria: Faint compact binary candidates within 300 pc.  \n- • ( FUV - 5 log 10 ( r est / 10)) > 14( FUV - NUV ) - 46\n- • r est < 300 pc  \nData Sources: Bailer-Jones et al. (2018) distance catalog ( r est ), GALEX (FUV, NUV)  \nTarget priority options: 1400  \nCadence options: bright 2x1, dark 2x1  \nA.6. mwm cb cvcandidates apogee  \nDescription of selection criteria: Bright AAVSO cataclysmic variables  \n- • Target in mos cataclysmic variables table\n- • H < 11  \nData Sources: 2MASS PSC (H)  \nTarget priority options: 1400  \nCadence options: bright 1x1  \nA.7. mwm cb cvcandidates boss  \nDescription of selection criteria: Faint AAVSO cataclysmic variables  \n- • Target in mos cataclysmic variables table\n- • H ≥ 11  \nData Sources: 2MASS PSC (H)  \nTarget priority options: 1400  \nCadence options: bright 2x1, dark 2x1  \nA.8. mwm cb gaiagalex apogee  \nDescription of selection criteria: Bright compact binary candidates using Gaia G and GALEX FUV color cut  \n- • ϖ/σ ϖ > 3\n- • G < 20\n- • FUV +5log1 10 ( ϖ/ 1000) + 5 > 1 . 5 + 1 . 28( FUV - G )\n- • H < 11  \nData Sources: Gaia DR2 (G, ϖ , σ ϖ ), 2MASS PSC (H), GALEX (FUV)  \nTarget priority options: 1400  \nCadence options: bright 1x1', 'A.9. mwm cb gaiagalex boss': "Description of selection criteria: Faint compact binary candidates using Gaia G and GALEX FUV color cut  \n- · ϖ/σ ϖ > 3\n- · G < 20\n- · FUV +5log 10 ( ϖ/ 1000) + 5 > 1 . 5 + 1 . 28( FUV -G )\n- · H ≥ 11  \nData Sources: Gaia DR2 (G, ϖ , σ ϖ ), 2MASS PSC (H), GALEX (FUV)  \nTarget priority options: 1400  \nCadence options: bright 2x1, dark 2x1  \nA.10. mwm cb uvex1  \nDescription of selection criteria: Gaia and GALEX cross-match, keeping the nearest match within 5 '' and removing objects with small proper motion and parallax. Color cuts utilize both FUV and NUV magnitudes. 'AB' indicates magnitudes transformed to AB magnitudes, and M G is Gaia absolute magnitude calculated with r est .  \n- · r lo ≤ 1500\n- · g vis per > 5\n- · Neither of the following two conditions are met\n- -(log 10 ( µ/σ µ ) < 0 . 301) AND ( ϖ/σ ϖ > -1 . 4996 log 10 ( µ/σ µ )-4 . 05) AND ( ϖ/σ ϖ < 1 . 4995 log 10 ( µ/σ µ ) + 4 . 05)\n- -(log 10 ( µ/σ µ )-0 . 301) 2 / 0 . 39794 2 +( ϖ/σ ϖ ) 2 / 4 . 5 2 ≤ 1\n- · NUV > -100\n- · FUV > -100\n- · σ NUV < 0 . 2\n- · σ FUV < 0 . 2\n- · M G > 4 . 09 OR M G > 4 . 5457( G BP -G RP ) + 4 . 0457\n- · M G > -1 . 11749253 × 10 -3 ( FUV -NUV ) 3 +1 . 53748615 × 10 -2 ( FUV -NUV ) 2 +3 . 66419895 × 10 -1 ( FUV -NUV ) + 2 . 20026639)\n- · ( FUV -G AB ) < 6 . 08 OR [( FUV -G AB ) < 11 . 82( G BP , AB -G RP , AB ) + 2 . 58 AND ( FUV -G AB ) < -0 . 79( G BP , AB -G RP , AB +9 . 21)]  \nData Sources: Gaia DR2 ( M G , G BP , G RP , µ , σ m u , ϖ , σ ϖ , r lo , g vis per), Bailer-Jones et al. (2018) distance catalog ( r est ), GALEX (NUV, FUV, σ NUV , σ FUV )  \nTarget priority options: 1400  \nCadence options: bright 1x1, dark 1x2, dark 1x3", 'A.11. mwm cb uvex2': "Description of selection criteria: Gaia and GALEX cross-match, keeping the nearest match within 5 '' and removing objects with small proper motion and parallax. Color cuts utilize only NUV magnitudes. 'AB' indicates magnitudes transformed to AB magnitudes, and M G is Gaia absolute magnitude calculated with r est .  \n- · r lo ≤ 1500\n- · g vis per > 5\n- · Neither of the following two conditions are met\n- -(log 10 ( µ/σ µ ) < 0 . 301) AND ( ϖ/σ ϖ > -1 . 4996 log 10 ( µ/σ µ )-4 . 05) AND ( ϖ/σ ϖ < 1 . 4995 log 10 ( µ/σ µ ) + 4 . 05)\n- -(log 10 ( µ/σ µ )-0 . 301) 2 / 0 . 39794 2 +( ϖ/σ ϖ ) 2 / 4 . 5 2 ≤ 1\n- · NUV > -100\n- · σ NUV < 0 . 2\n- · M G > 4 . 09 OR M G > 4 . 5457( G BP -G RP ) + 4 . 0457\n- · ( NUV -G AB < 2 . 25) OR [( NUV -G AB < 6 . 725( G BP , AB -G RP , AB) -1 . 735) AND ( NUV -G AB < -0 . 983( G BP , AB -G RP , AB +8 . 24)]  \nData Sources: Gaia DR2 ( M G , G AB , G BP , G BP , AB , G RP , G RP , AB , µ , σ m u , ϖ , σ ϖ , g vis per), Bailer-Jones et al. (2018) distance catalog ( r lo , r est ), GALEX (NUV, σ NUV )  \nTarget priority options: 1400  \nCadence options:  \nbright 1x1, dark 1x2, dark 1x3  \nA.12. mwm cb uvex3  \nDescription of selection criteria: Gaia and XMM-Newton Optical Monitor SUSS Catalog cross-match, keeping the nearest match with 3 '' and removing objects with small proper motion and parallax. Color and quality cuts utilize the XMM UVM2 band.  \n- · r lo ≤ 1500\n- · g vis per > 5\n- · Neither of the following two conditions are met\n- -(log 10 ( µ/σ µ ) < 0 . 301) AND ( ϖ/σ ϖ > -1 . 4996 log 10 ( µ/σ µ )-4 . 05) AND ( ϖ/σ ϖ < 1 . 4995 log 10 ( µ/σ µ ) + 4 . 05)\n- -(log 10 ( µ/σ µ )-0 . 301) 2 / 0 . 39794 2 +( ϖ/σ ϖ ) 2 / 4 . 5 2 ≤ 1\n- · The following conditions are all NOT met\n- -qflag bit 1, 7, 8, or 9 is set\n- -qflag bit 2, or 3 is set AND UVM2 signif < 10\n- · M G > 4 . 09 OR M G > 4 . 5457( G BP -G RP ) + 4 . 0457\n- · UVM2 AB -G AB < 2 . 25 OR [(UVM2 AB -G AB < 6) AND (UVM2 AB -G AB < 5 . 57377( G BP , AB -G RP , AB ) + 0 . 2049)]  \nData Sources: Gaia DR2 ( M G , G AB , G BP , G BP , AB , G RP , G RP , AB , µ , σ m u , ϖ , σ ϖ , g vis per), Bailer-Jones et al. (2018) distance catalog ( r lo , r est ), XMM OM SUSS v4.1(UVM2 AB , UVM2 signif , qflag)  \nTarget priority options: 1400  \nCadence options: bright 1x1, dark 1x2, dark 1x3  \nA.13. mwm cb uvex4  \nDescription of selection criteria: Gaia and Swift UVOT Catalog cross-match, keeping the nearest match with 3 '' and removing objects with small proper motion and parallax. Color cuts utilize the UVW2 band, and quality cuts utilize both UVW2 and UVW1  \n- · r lo ≤ 1500\n- · g vis per > 5\n- · UVW1 AB > -100\n- · UVW2 AB > -100\n- · Neither of the following two conditions are met\n- -(log 10 ( µ/σ µ ) < 0 . 301) AND ( ϖ/σ ϖ > -1 . 4996 log 10 ( µ/σ µ )-4 . 05) AND ( ϖ/σ ϖ < 1 . 4995 log 10 ( µ/σ µ ) + 4 . 05)\n- -(log 10 ( µ/σ µ )-0 . 301) 2 / 0 . 39794 2 +( ϖ/σ ϖ ) 2 / 4 . 5 2 ≤ 1\n- · The following conditions are all NOT met\n- -qflag bit 0 or 6 is set\n- -qflag bit 1, 2, or 5 is set AND UVW2 signif < 10\n- · M G > 4 . 09 OR M G > 4 . 5457( G BP -G RP ) + 4 . 0457\n- · UVW2 AB -G AB < 2 . 25 OR [(UVW2 AB -G AB < 6) AND (UVW2 AB -G AB < 5 . 57377(( G BP , AB -G RP , AB ) + 0 . 2049)]  \nData Sources: Gaia DR2 ( M G , G AB , G BP , G BP , AB , G RP , G RP , AB , µ , σ m u , ϖ , σ ϖ , g vis per), Bailer-Jones et al. (2018) distance catalog ( r lo , r est ), Swift UVOT(UVW1 AB , UVW2 AB , UVW2 signif , qflag2)  \nTarget priority options: 1400  \nCadence options: bright 1x1, dark 1x2, dark 1x3", 'A.14. mwm cb uvex5': "Description of selection criteria: Gaia and GALEX cross-match, keeping the nearest match within 5 '' and removing objects with small proper motion and parallax. Only objects with FUV and NUV detections are kept, but the color cuts utilize only optical colors and magnitudes. Here, the expected Gaia Main Sequence locus (GMS) is defined by GMS = 0 . 00206868742 x 6 +0 . 0401594518 x 5 -0 . 842512410 x 4 +4 . 89384979 x 3 -12 . 3826637 x 2 + 17 . 0197205 x -3 . 19987835, where x = G -G RP . M G is the Gaia absolute magnitude calculated with r est .  \n- · r lo ≤ 1500\n- · g vis per > 5\n- · Neither of the following two conditions are met\n- -(log 10 ( µ/σ µ ) < 0 . 301) AND ( ϖ/σ ϖ > -1 . 4996 log 10 ( µ/σ µ )-4 . 05) AND ( ϖ/σ ϖ < 1 . 4995 log 10 ( µ/σ µ ) + 4 . 05)\n- -(log 10 ( µ/σ µ )-0 . 301) 2 / 0 . 39794 2 +( ϖ/σ ϖ ) 2 / 4 . 5 2 ≤ 1\n- · NUV > -100\n- · FUV > -100\n- · σ NUV < 0 . 2\n- · σ FUV < 0 . 2\n- · M G > 4 . 0866\n- · H < 15\n- · | GMS -M G | ≤ 0 . 5\n- · r est < 0 . 51 × 10 0 . 2291 G  \nData Sources: Gaia DR2 ( M G , G RP , µ , σ m u , ϖ , σ ϖ , r lo , g vis per), Bailer-Jones et al. (2018) distance catalog ( r est ), GALEX (NUV, FUV, σ NUV , σ FUV ), 2MASS PSC (H)  \nTarget priority options:  \n1400  \nCadence options: bright 1x1, dark 1x2, dark 1x3", 'A.15. mwm dust core': "Description of selection criteria: The dust carton selects bright, nearby, midplane giants with the same quality cuts as Galactic Genesis (GG) to supplement GG targets in regions of high reddening. The Galaxy within 5 kpc and with | z | < 0 . 2 kpc is divided into 100 pc 3 regions ('voxels') and the number of GG targets in each voxel are counted. In voxels with fewer than 10 GG stars, 10 -n GG stars are selected for inclusion in this carton.  \n- · σ ϖ /ϖ < 0 . 2\n- · 1 /ϖ < 5 kpc\n- · | z | < 0 . 2 kpc (using ϖ -based distances)\n- · M K < 2 . 6, adopting A K = 0 . 918( H -4 . 5)\n- · ( J -K ) 0 > 0 . 5, where E ( J -K ) = 1 . 5 A K\n- · H < 11 . 2\n- · gal contam == 0\n- · cc flg == 0\n- · 0 < rd flag < = 3\n- · ph qual flag is A or B  \nData Sources: Gaia DR2 ( ϖ , σ ϖ ), 2MASS PSC (J, H, K, gal contam, cc flag, rd flag, ph qual)  \nTarget priority options: 2720  \nCadence options: bright 1x1  \nDescription of selection criteria: Optical counterpart in Gaia DR2 to a candidate compact binary detected by eROSITA, chosen as the possible counterpart with the smallest angular separation  \n- · G > 16\n- · L > 8 in at least one of the three eROSITA energy bands  \n- · Detections in three eROSITA energy bands\n- · log ( f x /f opt ) < 2 . 7\n- · radec err > 0 and s / radec err < 2 . 1, where s is the separation between the Gaia and eROSITA sources\n- · Neither of the following two conditions are met\n- -(log 10 ( µ/σ µ ) < 0 . 301) AND ( ϖ/σ ϖ > -1 . 4996 log 10 ( µ/σ µ )-4 . 05) AND ( ϖ/σ ϖ < 1 . 4995 log 10 ( µ/σ µ ) + 4 . 05)\n- -(log 10 ( µ/σ µ )-0 . 301) 2 / 0 . 39794 2 +( ϖ/σ ϖ ) 2 / 4 . 5 2 ≤ 1\n- · Is the optical source that meets the above criteria with the smallest separation s  \nData Sources: eROSITA ( f x , L , radec err), Gaia DR2 ( G , µ , σ m u , ϖ , σ ϖ , f opt (from G ))  \nTarget priority options: 1910, 2400  \nCadence options: bright 1x1, dark 1x2, dark 1x3  \nA.17.  \nmwm erosita compact var  \nDescription of selection criteria: Optical counterpart to a candidate compact binary detected by eROSITA, chosen  \nas the possible counterpart with the largest variability in Gaia DR2  \n- · G > 16\n- · L > 8 in at least one of the three eROSITA energy bands\n- · Detections in three eROSITA energy bands\n- · log ( f x /f opt ) < 2 . 7\n- · radec err > 0 and s / radec err < 2 . 1, where s is the separation between the Gaia and eROSITA sources\n- · Neither of the following two conditions are met\n- -(log 10 ( µ/σ µ ) < 0 . 301) AND ( ϖ/σ ϖ > -1 . 4996 log 10 ( µ/σ µ )-4 . 05) AND ( ϖ/σ ϖ < 1 . 4995 log 10 ( µ/σ µ ) + 4 . 05)\n- -(log 10 ( µ/σ µ )-0 . 301) 2 / 0 . 39794 2 +( ϖ/σ ϖ ) 2 / 4 . 5 2 ≤ 1\n- · Is the optical source that meets the above criteria with the largest variability log 10 ( ( phot g n obs phot g mean flux over error ) 1 / 2 )  \nData Sources: eROSITA ( f x , L , radec err), Gaia DR2 ( G , µ , σ m u , ϖ , σ ϖ , f opt (from G ), phot g n obs, phot g mean flux over error)  \nTarget priority options: 1900, 2400  \nCadence options: bright 1x1, dark 1x2, dark 1x3  \nA.18. mwm erosita stars  \nDescription of selection criteria: Optical or infrared counterpart to a candidate stellar source detected by eROSITA. Counterpart identified using the techniques and data described in Freund et al. (2022).  \nData Sources: eROSITA, Gaia DR2, 2MASS PSC  \nTarget priority options: 1920, 2400  \nCadence options: bright 1x1, dark 1x2, dark 1x3  \nA.19. mwm galactic core  \nDescription of selection criteria: A simple color-magnitude cut effectively targets luminous cool giant stars (median(log g ) ∼ 1 . 0 -1 . 5) with little ( < 6%) contamination from dwarf stars.  \n- · H < 11\n- · G -H > 3 . 5 or Gaia non-detection\n- · gal contam == 0\n- · cc flg == 0\n- · 0 < rd flag < = 3\n- · ph qual flag is A or B  \nGaia DR2 (G), 2MASS PSC (H, gal contam, cc flg, rd flag, ph qual)  \nData Sources: Target priority options: 2710 Cadence options: bright 1x1  \nA.20. mwm legacy ir2opt  \nDescription of selection criteria: This carton selects all bright Gaia objects that are in APOGEE DR16 (in particular the sdss apogeeallstarmerge r13 file) to be observed with BOSS.  \n- · 3 < G < 18\n- · G BP > 13\n- · G RP > 13.  \nData Sources: Gaia DR2 (G, G , G  \nTarget priority options: 6100  \nCadence options:  \nBP RP ), APOGEE DR16 bright 1x1  \nA.21. mwm ob cepheids  \nDescription of selection criteria: Catalog of Cepheids compiled by Inno et al. (2021)  \nData Sources: Inno et al. (2021)  \nTarget priority options:  \n2910  \nCadence options: bright 3x1  \nA.22. mwm ob core  \nDescription of selection criteria: This carton uses color and magnitude cuts to select hot, young stars.  \n- · ϖ < 10 (10 -K -0 . 61) / 5)\n- · G < 16\n- · J -K -0 . 25( G -K ) < 0 . 10\n- · J -K -0 . 25( G -K ) > -0 . 30\n- · J -H < 0 . 15( G -K ) + 0 . 05\n- · J -H > 0 . 15( G -K ) -0 . 15\n- · J -K < 0 . 23( G -K ) + 0 . 03\n- · G > 2( G -K ) + 3 . 0\n- · Cross match separation < 1 ''\n- · RUWE < 1 . 4  \nData Sources: Gaia DR2 (G, ϖ , RUWE), 2MASS PSC (J, H, K)  \nTarget priority options: 2910  \nCadence options: bright 3x1  \nA.23. mwm rv long fps  \nDescription of selection criteria: This carton selects stars previously observed at least 3 times with the APOGEE instrument if it was targeted as part of the main APOGEE sample or the APOGEE-2 binary program.  \n- · Presence in sdss apogeeallstarmerge r13 file (previously observed with APOGEE 1 and/or 2\n- · APOGEE number of visits ≥ 3\n- · H < 11 . 5\n- · APOGEE TARGFLAGS includes one of the following: APOGEE SHORT, APOGEE INTERMEDIATE, APOGEE LONG, APOGEE2 BIN  \n- · Gaia-based distance  \nData Sources:  \nAPOGEE, 2MASS PSC (H), Gaia DR 2  \nTarget priority options: 2510, 2520, 2530, 2540  \nCadence options: bright 6x1 bright 6x2, bright 9x1, bright 9x2, bright 12x1, bright 12x2, bright 15x1, bright 15x2", 'A.24. mwm rv short fps': "Description of selection criteria: This carton selects stars that were never previously observed with APOGEE and applies the same color and quality cuts as the main APOGEE surveys.  \n- · H < 10 . 8\n- · J -K s -(1 . 5 · 0 . 918( H -W 2-0 . 05)) > = 0 . 05\n- · J msigcom,H msigcom,K s msigcom ≤ 0 . 1\n- · W 2 sigmpro ≤ 0 . 1\n- · 2MASS ph qual any of the following: AAA, AAB, ABA, BAA, ABB, BAB, BBA, BBB\n- · 2MASS gal contam = 0\n- · 2MASS cc flg = 0\n- · 2MASS rd flg any of the following: 111, 112, 121, 211, 122, 212, 221, 222\n- · 2MASS prox ≥ 6\n- · Gaia DR2 parallax exists\n- · Does not match a source in the 2MASS extended catalog  \nData Sources: 2MASS PSC (J, H, K s , J msigcom, H msigcom, K s msigcom, ph qual, gal contam, cc flg, rd flg, prox), Gaia DR 2, AllWise (W2)  \nTarget priority options: 2515, 2525, 2535, 2545  \nCadence options: bright 18x1  \nA.25. mwm snc 100pc apogee  \nDescription of selection criteria: Infrared bright targets in the 100 pc volume limited region.  \n- · ϖ -σ ϖ > 10\n- · H < 11\n- · astrometric excess noise < 2 if in one of the following regions\n- -l ≤ 180 AND b < -0 . 139 l +25 AND b > 0 . 139 l -25\n- -l > 180 AND b > -0 . 139 l +25 AND b < 0 . 139 l -25\n- -√ ( l -303 . 2) 2 +2 ∗ ( b +44 . 4) 2 < 5\n- -√ ( l -280 . 3) 2 +2 ∗ ( b +33 . 0) 2 < 8  \nData Sources: Gaia DR2 ( ϖ , σ ϖ , astrometric excess noise, l , b ), 2MASS PSC (H)  \nTarget priority options: 1805  \nCadence options: bright 1x1  \nA.26. mwm snc 100pc boss  \nDescription of selection criteria: Optically bright targets in the 100 pc volume limited region.  \n- · ϖ -σ ϖ > 10\n- · astrometric excess noise < 2 if in one of the following regions\n- -l ≤ 180 AND b < -0 . 139 l +25 AND b > 0 . 139 l -25\n- -l > 180 AND b > -0 . 139 l +25 AND b < 0 . 139 l -25\n- -√ ( l -303 . 2) 2 +2 ∗ ( b +44 . 4) 2 < 5\n- -√ ( l -280 . 3) 2 +2 ∗ ( b +33 . 0) 2 < 8  \nData Sources: Gaia DR2 ( ϖ , σ ϖ , astrometric excess noise, l , b , G)  \nTarget priority options: 1800  \nCadence options: bright 2x1, dark 2x1  \nA.27. mwm snc 250pc apogee  \nDescription of selection criteria: Infrared bright targets in the 250 pc volume limited region.  \n- · G +5log 10 ( ϖ/ 1000) + 5 < 6\n- · ϖ -σ ϖ > 4\n- · H < 11\n- · astrometric excess noise < 2 if in one of the following regions\n- -l ≤ 180 AND b < -0 . 139 l +25 AND b > 0 . 139 l -25\n- -l > 180 AND b > -0 . 139 l +25 AND b < 0 . 139 l -25\n- -√ ( l -303 . 2) 2 +2 ∗ ( b +44 . 4) 2 < 5\n- -√ ( l -280 . 3) 2 +2 ∗ ( b +33 . 0) 2 < 8  \nData Sources: Gaia DR2 ( ϖ , σ , astrometric excess noise, l , b , G), 2MASS PSC (H)  \nTarget priority options:  \nϖ 1815  \nCadence options: bright 1x1  \nA.28. mwm snc 250pc boss  \nDescription of selection criteria: Optically bright targets in the 250 pc volume limited region.  \n- · G +5log 10 ( ϖ/ 1000) + 5 < 6\n- · ϖ -σ ϖ > 4\n- · astrometric excess noise < 2 if in one of the following regions\n- -l ≤ 180 AND b < -0 . 139 l +25 AND b > 0 . 139 l -25\n- -l > 180 AND b > -0 . 139 l +25 AND b < 0 . 139 l -25\n- -√ ( l -303 . 2) 2 +2 ∗ ( b +44 . 4) 2 < 5\n- -√ ( l -280 . 3) 2 +2 ∗ ( b +33 . 0) 2 < 8  \nData Sources: Gaia DR2 ( ϖ , σ , astrometric excess noise, l , b  \nϖ , G), 2MASS PSC (H)  \nTarget priority options: 1810  \nCadence options: bright 2x1, dark 2x1  \nA.29. mwm tess planet  \nDescription of selection criteria: Stars with TESS 2-minute cadence data taken during the nominal 2 year mission, prioritizing those that are either TESS Objects of Interest (TOIs) or Community TESS Objects of Interest (CTOIs)  \n- · 7 < H < 12  \nData Sources: 2MASS PSC (H), TESS  \nTarget priority options: 2600, 2605, 2610  \nCadence options: bright 1x1, bright 1x2, bright 1x3, bright 1x4, bright 1x5, bright 1x6  \nA.30. mwm tessrgb core  \nDescription of selection criteria: This carton selects red giant candidates with a color cut and uses a magnitude cut to limit stars likely to have stellar oscillations detectable in TESS light curve data.  \n- · J -K > 0 . 5\n- · H < 12\n- · T < 13\n- · H -10 + 5 log 10 ϖ < 1  \n- · | b | > 20  \nData Sources: Gaia DR2 ( ϖ  \n), 2MASS PSC (J, H, K), TESS (T)  \nTarget priority options: 2800  \nCadence options: bright 1x1, bright 1x2, bright 1x3, bright 1x4, bright 1x5, bright 1x6  \nA.31. mwm wd core  \nDescription of selection criteria: All sufficiently bright white dwarf candidates, where P WD is the probability a target is a white dwarf  \n- · G < 20\n- · P WD > 0 . 5  \nData Sources: Gaia DR2 (G), Gentile Fusillo et al. (2019, P WD )  \nTarget priority options: 1400  \nCadence options: dark 2x1  \nA.32. mwm yso cluster apogee  \nDescription of selection criteria: Infrared bright YSO candidates associated with young moving groups, as identified by Kounkel et al. (2020).  \n- · H < 13\n- · age < 10 7 . 5 years  \nData Sources: 2MASS PSC (H), Kounkel et al. (2020, age)  \nTarget priority options: 2705  \nCadence options: bright 3x1  \nA.33. mwm yso cluster boss  \nDescription of selection criteria: Optically bright YSO candidates associated with young moving groups, as identified by Kounkel et al. (2020).  \n- · G RP < 15 . 5\n- · age < 10 7 . 5 years  \nData Sources: Gaia DR2 ( G RP ), Kounkel et al. (2020, age)  \nTarget priority options: 2705  \nCadence options: bright 3x1, bright 4x1, bright 5x1, bright 6x1  \nA.34. mwm yso cmz apogee  \nDescription of selection criteria: YSOs in the central molecular zone (CMZ), the most extreme star-forming environment in the Milky Way  \n- · H < 13\n- · [8 . 0] -[24] > 2 . 5, in Gutermuth & Heyer (2015) catalog\n- · ϖ < 0 . 2 or not measured  \nData Sources: Gaia DR2 ( ϖ ), 2MASS PSC (H), Spitzer ([8.0], [24])  \nTarget priority options: 2700  \nCadence options:  \nbright 3x1  \nRP ), AllWise (W1, W2, W3, W4) 2705  \nA.35. mwm yso disk apogee  \nDescription of selection criteria: YSO's expected to have protoplanetary disks, as identified by larger infrared excesses.  \n- · H < 13\n- · W 1 -W 2 > 0 . 25\n- · W 2 -W 3 > 0 . 50\n- · W 3 -W 4 > 1 . 50\n- · ϖ > 0 . 3 mas  \nData Sources: Gaia DR2 ( ϖ  \nTarget priority options:  \nCadence options:  \n), 2MASS PSC (H), AllWise (W1, W2, W3, W4) 2705 bright 3x1  \nA.36. mwm yso disk boss  \nDescription of selection criteria: Optically bright YSO's expected to have protoplanetary disks, as identified by larger infrared excesses.  \n- · G RP < 8 . 5\n- · W 1 -W 2 > 0 . 25\n- · W 2 -W 3 > 0 . 50\n- · W 3 -W 4 > 1 . 50\n- · ϖ > 0 . 3 mas  \nData Sources: Gaia DR2 ( G , ϖ  \nTarget priority options:  \nCadence options: bright 3x1, bright 4x1, bright 5x1, bright 6x1  \nA.37. mwm yso embedded apogee  \nDescription of selection criteria: Deeply embedded YSO candidates too optically faint for parallax measurements have more stringent infrared color cuts to avoid contamination with reddened field stars.  \n- · H < 13\n- · G > 18 . 5 or undetected\n- · J -H > 1\n- · H -K > 0 . 5\n- · W 1 -W 2 > 0 . 5\n- · W 2 -W 3 > 1\n- · W 3 -W 4 > 1 . 5\n- · W 3 -W 4 > 0 . 8( W 1 -W 2) + 1 . 1  \nData Sources: Gaia DR2 (G), 2MASS PSC (J, H, K), AllWise (W1, W2, W3, W4)  \nTarget priority options: 2705  \nCadence options: bright 3x1  \nA.38. mwm yso nebula apogee  \nDescription of selection criteria: YSO's with strong nebular emission should saturate in the long AllWise bands and are identified with short wavelength color cuts.  \n- · H < 13\n- · (no W4 AND W 2 -W 3 > 4) OR (no W3, W4 AND J -H > 1 . 1)\n- · b < 5 ·\n- · b > -5 · OR l > 180 ·  \nData Sources: 2MASS PSC (J, H), AllWise (W1, W2, W3, W4)  \nTarget priority options: 2705 Cadence options: bright 3x1  \nA.39. mwm yso pms apogee  \nDescription of selection criteria: Infrared bright YSO candidates based on their location above the main sequence, as identified by Zari et al. (2018) or McBride et al. (2021).  \n- · H < 13  \nData Sources: 2MASS PSC (H)  \nTarget priority options: 2700  \nCadence options: bright 3x1  \nA.40. mwm yso pms boss  \nDescription of selection criteria: Optically bright YSO candidates based on their location above the main sequence, as identified by Zari et al. (2018) or McBride et al. (2021).  \n- · G RP < 15 . 5  \nData Sources: Gaia DR2 ( G RP )  \nTarget priority options: 2700  \nCadence options: bright 3x1, bright 4x1, bright 5x1, bright 6x1  \nA.41. mwm yso variable apogee  \nDescription of selection criteria: YSO candidates that are variable in the Gaia bands, to be observed with APOGEE. Variability in a given band X is defined by V X = √ N obs σ I X / ( I X ), where I X is the mean flux and σ I X its associated error. Below, M X = G X -5(log 10 (1000 /ϖ ) -1)  \n- · H < 13\n- · G < 18 . 5\n- · ϖ > 0 . 3\n- · V G > 0 . 02\n- · V BP > 0 . 02\n- · V RP > 0 . 02\n- · V 0 . 75 G < V BP < V G\n- · 0 . 75 V G < V RP < V 0 . 95 G\n- · G BP -G RP > 1 . 3\n- · M BP > 5 log 10 V BP +11\n- · 2 . 5( G BP -G RP ) -1 < M G < 2 . 5 ∗ ( G BP -G RP ) + 2 . 5  \nData Sources: Gaia DR2 (G, G RP , G BP , ϖ , I X , σ I X  \nTarget priority options: 2705  \nCadence options: bright 3x1  \nA.42. mwm yso variable boss  \nDescription of selection criteria: YSO candidates that are variable in the Gaia bands, to be observed with BOSS.  \nVariability in a given band X is defined by V X = √ N obs σ I X / ( I X ), where I X is the mean flux and σ I X its associated error. Below, M X = G X -5(log 10 (1000 /ϖ ) -1)  \n- · H < 13\n- · G < 18 . 5  \n), 2MASS PSC (H)  \n- · ϖ > 0 . 3\n- · V G > 0 . 02\n- · V BP > 0 . 02\n- · V RP > 0 . 02\n- · V 0 . 75 G < V BP < V G\n- · 0 . 75 V G < V RP < V 0 . 95 G\n- · G BP -G RP > 1 . 3\n- · M BP > 5 log 10 V BP +11\n- · 2 . 5( G BP -G RP ) -1 < M G < 2 . 5 ∗ ( G BP -G RP ) + 2 . 5  \nData Sources: Gaia DR2 (G, G RP , G BP , ϖ , I X , σ I X ), 2MASS PSC (H)  \nTarget priority options: 2705  \nCadence options: bright 3x1, bright 4x1, bright 5x1, bright 6x1", 'B. DETAILS OF BHM V0.5.3 TARGET CARTONS': "In this appendix we provide a more detailed description of the full set of BHM target cartons that are being released as part of SDSS DR18. We describe not only the 'core' BHM cartons in Table 4, but also all ancillary/supplementary BHM cartons, which collectively expand the scope, footprint, and depth of the project beyond the core science goals. We remind the reader that inclusion in a carton means that the target fits the carton selection criteria, not that it is guaranteed to be observed.  \nFor each target carton, we provide the following information: The target selection plan and target selection tag codes give the software and configuration versions of the target selection code that were used in this carton instance. In Summary , we provide a short synopsis of the content of the target carton, followed by a Simplified description of selection criteria with a human-readable description of the specific selection criteria that have been applied to build the carton, including quantitative limits on colors, magnitudes, and other quantities. The Target priority options and Cadence options indicate which 'priority' and 'cadence' option(s) have been allocated to the targets in this carton. Targets with numerically smaller priority are more likely to be assigned fibers; the cadence describes a target's exposure time requirement. Under Implementation , we point to the specific section of the target selection Python code that implements this carton 21 . Finally, the Number of targets lists the number of targets which pass all of the carton selection criteria. Note that targets are often shared between two or more cartons.  \nB.1. bhm aqmes med  \ntarget selection plan:  \n0.5.0  \ntarget selection tag: 0.3.0  \nSummary: Spectroscopically confirmed optically bright SDSS QSOs, selected from the SDSS QSO catalog (DR16Q, Lyke et al. 2020). Located in 36 mostly disjoint fields within the SDSS QSO footprint that were pre-selected to contain higher than average numbers of bright QSOs and CSC targets. The list of field centers can be found within the target selection repository.  \nSimplified description of selection criteria: Select all objects from SDSS DR16 QSO catalog that have SDSS 16 . 0 < i psf < 19 . 1 AB, and that lie within 1.49 degrees of at least one AQMES-medium field location.  \nTarget priority options:  \n1100  \nCadence options:  \ndark 10x4 4yr  \nImplementation:  \nbhm aqmes.py  \nNumber of targets:  \n2663  \nB.2. bhm aqmes med faint  \ntarget selection plan:  \n0.5.0  \ntarget selection tag: 0.3.0  \nSummary: Spectroscopically confirmed optically faint SDSS QSOs, selected from the SDSS QSO catalog (DR16Q, Lyke et al. 2020). Located in 36 mostly disjoint fields within the SDSS QSO footprint that were pre-selected to contain higher than average numbers of bright QSOs and CSC targets. The list of field centres can be found within the target selection repository.  \nSimplified description of selection criteria: Select all objects from SDSS DR16 QSO catalog that have SDSS 19 . 1 < i psf < 21 . 0 AB, and that lie within 1.49 degrees of at least one AQMES-medium field location.  \nTarget priority options: 3100  \nCadence options:  \ndark 10x4 4yr  \nImplementation:  \nbhm aqmes.py  \nNumber of targets:  \n16853  \nB.3. bhm aqmes wide2  \ntarget selection plan:  \n0.5.4  \ntarget selection tag:  \n0.3.5  \nSummary: Spectroscopically confirmed optically bright SDSS QSOs, selected from the SDSS QSO catalog (DR16Q, Lyke et al. 2020). Located in 425 fields within the SDSS QSO footprint, where the choice of survey area prioritized field that overlapped with the SPIDERS footprint (approx 180 < l < 360 deg), and/or had higher than average numbers of bright QSOs and CSC targets. The list of field centers can be found within the target selection repository.  \nSimplified description of selection criteria: Select all objects from SDSS DR16 QSO catalog that have SDSS 16 . 0 < i psf < 19 . 1 AB, and that lie within 1.49 degrees of at least one AQMES-wide field location.  \nTarget priority options:  \n1210, 1211  \nCadence options:  \ndark 2x4  \nImplementation:  \nbhm aqmes.py  \nNumber of targets:  \n24142  \nB.4. bhm aqmes wide2 faint  \ntarget selection plan:  \n0.5.4  \ntarget selection tag:  \n0.3.5  \nSummary: Spectroscopically confirmed optically faint SDSS QSOs, selected from the SDSS QSO catalog (DR16Q, Lyke et al. 2020). Located in 425 fields within the SDSS QSO footprint, where the choice of survey area prioritized field that overlapped with the SPIDERS footprint (approx 180 < l < 360 deg), and/or had higher than average numbers of bright QSOs and CSC targets. The list of field centres can be found within the target selection repository.  \nSimplified description of selection criteria: Select all objects from SDSS DR16 QSO catalog that have SDSS 19 . 1 < i psf < 21 . 0 AB, and that lie within 1.49 degrees of at least one AQMES-wide field location.  \nTarget priority options:  \n3210, 3211  \nCadence options:  \ndark 2x4  \nImplementation:  \nbhm aqmes.py  \nNumber of targets:  \n99586  \nB.5. bhm aqmes bonus core  \ntarget selection plan:  \n0.5.4  \ntarget selection tag:  \n0.3.5  \nSummary: Spectroscopically confirmed optically bright SDSS QSOs, selected from the SDSS QSO catalog (DR16Q; Lyke et al. 2020). Located anywhere within the SDSS DR16Q footprint.  \nSimplified description of selection criteria: Select all objects from SDSS DR16 QSO catalog that have SDSS 16 . 0 < i psf < 19 . 1 AB.  \nTarget priority options:  \n3300,3301  \nCadence options:  \ndark 1x4  \nImplementation:  \nbhm aqmes.py  \nNumber of targets:  \n83163  \ntarget selection plan:  \n0.5.4  \ntarget selection tag:  \n0.3.5  \nSummary: Spectroscopically confirmed optically faint SDSS QSOs, selected from the SDSS QSO catalog (DR16Q; Lyke et al. 2020). Located anywhere within the SDSS DR16Q footprint.  \nSimplified description of selection criteria: Select all objects from SDSS DR16 QSO catalog that have SDSS 19 . 1 < i psf < 21 . 0 AB.  \nTarget priority options:  \n3302,3303  \nCadence options:  \ndark 1x4  \nImplementation:  \nbhm aqmes.py  \nNumber of targets:  \n424163  \ntarget selection plan:  \n0.5.4  \ntarget selection tag:  \n0.3.5  \nSummary: Spectroscopically confirmed, extremely optically bright SDSS QSOs, selected from the SDSS QSO catalog (DR16Q; Lyke et al. 2020). Located anywhere within the SDSS DR16Q footprint.  \nSimplified description of selection criteria: Select all objects from SDSS DR16 QSO catalog that have SDSS 14 . 0 < i psf < 18 . 0 AB.  \nTarget priority options:  \n4040,4041  \nCadence options:  \nbright 3x1  \nImplementation:  \nbhm aqmes.py  \nNumber of targets:  \n10848  \ntarget selection plan:  \n0.5.0  \ntarget selection tag:  \n0.3.0  \nSummary: A supporting sample of candidate QSOs that have been selected by the Gaia-unWISE AGN catalog (Shu et al. 2019) and/or the SDSS XDQSO catalog (Bovy et al. 2011). These targets are located within five (+1 backup) well known survey fields (SDSS-RM, COSMOS, XMM-LSS, ECDFS, CVZ-S/SEP, and ELIAS-S1).  \nSimplified description of selection criteria: Starting from a parent catalog of optically selected objects in the RM fields (as presented by Yang & Shen 2022), select candidate QSOs that satisfy all of the following: i) are identified via external ancillary methods (photo bitmask & 3 != 0); ii) have 15 < i psf < 21 . 5 AB (or 16 < G < 21 . 7 Vega in the CVZ-S/SEP field, photometry taken from Yang & Shen 2022); iii) do not have significant detections ( > 3 σ ) of parallax and/or proper motion in Gaia DR2; iv) are not vetoed due to results of visual inspections of recent spectroscopy; and v) do not lie in the SDSS-RM field.  \nTarget priority options:  \n900-1050  \nCadence options:  \ndark 174x8, dark 100x8  \nImplementation:  \nbhm rm.py  \nNumber of targets:  \n943  \nB.6. bhm aqmes bonus faint  \nB.7. bhm aqmes bonus bright  \nB.8. bhm rm ancillary  \ntarget selection plan:  \n0.5.0 0.3.0  \ntarget selection tag:  \nSummary: A sample of candidate QSOs selected via the methods presented by Yang & Shen (2022). These targets are located within five (+1 backup) well known survey fields (SDSS-RM, COSMOS, XMM-LSS, ECDFS, CVZ-S/SEP, and ELIAS-S1).  \nSimplified description of selection criteria: Starting from a parent catalog of optically selected objects in the RM fields (as presented by Yang & Shen 2022), select candidate QSOs that satisfy all of the following: i) are identified via the Skew-T algorithm (skewt qso == 1); ii) have 17 < i psf < 21 . 5 AB (or 16 < G < 21 . 7 Vega in the CVZ-S/SEP field, photometry taken from Yang & Shen 2022); iii) do not have significant detections ( > 3 σ ) of parallax and/or proper motion in Gaia DR2; iv) are not vetoed due to results of visual inspections of recent spectroscopy; v) have detections in all of the gri bands (a Gaia detection is sufficient in the CVZ-S/SEP field); and vi) do not lie in the SDSS-RM field.  \nTarget priority options:  \n900-1050  \nCadence options:  \ndark 174x8, dark 100x8  \nImplementation:  \nbhm rm.py  \nNumber of targets:  \n3721  \nB.10. bhm rm var  \ntarget selection plan:  \n0.5.0  \ntarget selection tag:  \n0.3.0  \nSummary: A sample of candidate QSOs selected via their optical variability properties, as presented by Yang & Shen (2022). These targets are located within five (+1 backup) well known survey fields (SDSS-RM, COSMOS, XMM-LSS, ECDFS, CVZ-S/SEP, and ELIAS-S1).  \nSimplified description of selection criteria: Starting from a parent catalog of optically selected objects in the RM fields (as presented by Yang & Shen 2022), select candidate QSOs that satisfy all of the following: i) have significant variability in the DES or PanSTARRS1 multi-epoch photometry (var sn[ g ] > 3 and var rms[ g ] > 0 . 05); ii) have 17 < i psf < 20 . 5 AB (or 16 < G < 21 . 7 Vega in the CVZ-S/SEP field, photometry taken from Yang & Shen 2022); iii) do not have significant detections ( > 3 σ ) of parallax and/or proper motion in Gaia DR2; iv) are not vetoed due to results of visual inspections of recent spectroscopy; and v) do not lie in the SDSS-RM field.  \nTarget priority options:  \n900-1050  \nCadence options:  \ndark 174x8, dark 100x8  \nImplementation:  \nbhm rm.py  \nNumber of targets:  \n934  \nB.11. bhm rm known spec  \ntarget selection plan:  \n0.5.0  \ntarget selection tag:  \n0.3.0  \nSummary: A sample of known QSOs identified through optical spectroscopy from various projects, as collated by Yang & Shen (2022). These targets are located within five (+1 backup) well known survey fields (SDSS-RM, COSMOS, XMM-LSS, ECDFS, CVZ-S/SEP, and ELIAS-S1).  \nSimplified description of selection criteria: Starting from a parent catalog of optically selected objects in the RM fields (as presented by Yang & Shen 2022), select targets which satisfy all of the following: i) are flagged as having a spectroscopic identification (in the parent catalog or in the bhm rm tweaks table); ii) have 15 < i psf < 21 . 7 AB (SDSS-RM, CDFS, ELIAS-S1 fields), 15 < i psf < 21 . 5 AB (COSMOS and XMM-LSS fields), 16 < G < 21 . 7 Vega in the CVZ-S/SEP field (photometry taken from Yang & Shen 2022); iii) have a spectroscopic redshift in the range 0.005 < z < 7; and iv) are not vetoed due to results of visual inspections of recent spectroscopy.  \nTarget priority options:  \n900-1050  \nCadence options:  \ndark 174x8, dark 100x8  \nImplementation:  \nbhm rm.py  \nNumber of targets:  \n3022  \nB.12. bhm csc apogee  \ntarget selection plan:  \n0.5.15  \ntarget selection tag:  \n0.3.14  \nSummary:  \nX-ray sources from the CSC2.0 source catalog with NIR counterparts in 2MASS PSC  \nSimplified description of selection criteria: Starting from the parent catalog of CSC2.0 sources associated with optical/IR counterparts ( bhm csc v2 ). Select entries satisfying the following criteria: i) NIR counterpart is from the 2MASS catalog, ii) 2MASS H -band magnitude measurement is not null and in the accepted range for SDSS-V: 7 . 0 < H < 14 . 0. Allocate cadence (exposure time) requests based on H magnitude.  \nTarget priority options: 2930-2939  \nCadence options:  \nbright 1x1,bright 3x1  \nImplementation:  \nbhm csc.py  \nNumber of targets: 48928  \ntarget selection plan:  \n0.5.15  \ntarget selection tag:  \n0.3.14  \nSummary: X-ray sources from the CSC2.0 source catalog with counterparts in Panstarrs1-DR1 or Gaia DR2. Simplified description of selection criteria: Starting from the parent catalog of CSC2.0 sources associated with optical/IR counterparts ( bhm csc v2 ). Select entries satisfying the following criteria: i) optical counterpart is from the PanSTARRS1 or Gaia DR2 catalogs, ii) optical flux/magnitude is in the accepted range for SDSS-V: PanSTARRS1 g psf , r psf , i psf , z psf > 13 . 5 AB, and non-Null i psf (objects with PanSTARRS1 counterparts); G,G RP > 13 . 0 Vega (Gaia DR2 counterparts). Deprioritize targets which already have good quality SDSS spectroscopy. Allocate cadence (exposure time) requests based on optical brightness (PanSTARRS1 i psf or Gaia G ).  \nTarget priority options: 1920-1939, 2920-2939  \nCadence options:  \nbright 1x1,dark 1x2,dark 1x4  \nImplementation:  \nbhm csc.py  \nNumber of targets:  \n122731  \nB.14. bhm gua bright  \ntarget selection plan:  \n0.5.0  \ntarget selection tag:  \n0.3.0  \nSummary: A sample of optically bright candidate AGN lacking spectroscopic confirmations, derived from the parent sample presented by Shu et al. (2019), who applied a machine-learning approach to select QSO candidates from a combination of the Gaia DR2 and unWISE catalogs.  \nSimplified description of selection criteria: Starting with the Shu et al. (2019) catalog, select targets that satisfy the following criteria: i) have a Random Forest probability of being a QSO of > 0.8, ii) are in the magnitude range suitable for BOSS spectroscopy in bright time ( G dered > 13 . 0 and G RP, dered > 13 . 5, as well as G dered < 18 . 5 or G RP, dered < 18 . 5 Vega), and iii) do not have good optical spectroscopic measurements from a previous iteration of SDSS.  \nTarget priority options:  \n4040  \nCadence options:  \nbright 2x1  \nImplementation:  \nbhm gua.py  \nNumber of targets:  \n254601  \ntarget selection plan:  \n0.5.16  \ntarget selection tag:  \n0.3.13  \nSummary: A supplementary magnitude limited sample of optically bright galaxies selected from the DESI Legacy Survey DR8 optical/IR imaging catalog. Selection is based on optical morphology, lack of Gaia DR2 parallax, and several magnitude cuts.  \nSimplified description of selection criteria: Starting from the DESI Legacy Survey DR8 catalog (lsdr8), select entries satisfying all of the following criteria: i) lsdr8 morphological type != 'PSF', ii) zero or Null parallax in Gaia DR2, iii) z model , dered < 19 . 0 AB, and z fiber , dered < 19 . 5 AB, and z fiber < 19 . 0 AB, and r fiber > 16 . 0 AB, and G > 15 . 0 Vega, and G RP > 15 . 0 Vega (photometry from lsdr8).  \nTarget priority options:  \n7100  \nCadence options:  \nbright 1x1, dark 1x1, dark 1x4  \nImplementation:  \nbhm galaxies.py  \nNumber of targets:  \n7320203  \nB.17. bhm spiders agn lsdr8  \ntarget selection plan:  \n0.5.0  \ntarget selection tag:  \n0.3.0  \nSummary: This is the highest priority carton for SPIDERS AGN wide area follow up. The carton provides optical counterparts to point-like (unresolved) X-ray sources detected in early reductions of the first 6-months of eROSITA all sky survey data (eRASS:1). The sample is expected to contain a mixture of QSOs, AGN, stars and compact objects. The X-ray sources have been cross-matched by the eROSITA-DE team to DESI Legacy Survey DR8 (lsdr8) optical/IR counterparts. All targets are located in the sky hemisphere where MPE controls the data rights (approx. 180 < l < 360 deg). Due to the footprint of lsdr8, nearly all targets in this carton are located at high Galactic latitudes ( | b | > 15 deg).  \nSimplified description of selection criteria: Starting from a parent catalog of eRASS:1 point source → legacysurvey.org/dr8 associations (method: NWAY assisted by optical/IR priors computed via a pre-trained Random Forest, building on Salvato et al. 2022), select targets which meet all of the following criteria: i) have eROSITA detection likelihood > 6.0, ii) have an X-ray → optical/IR cross-match probability (NWAY) of p any > 0.1, iii) have 13 . 5 < r fibertot < 22 . 5 or 13 . 5 < z fibertot < 21 . 0 AB, iv) are not saturated in Legacy Survey imaging, v) have at least one observation in r-band and at least one observation in g- or z-band, and vi) if detected by Gaia DR2 then have G > 13 . 5 and G RP > 13 . 5 Vega (photometry from lsdr8). We deprioritize targets if any of the following criteria are met: a) the target already has existing good quality SDSS spectroscopy, b) the X-ray detection likelihood is < 8.0,  \ntarget selection plan:  \n0.5.0 0.3.0  \ntarget selection tag:  \nSummary: A sample of optically faint candidate AGN lacking spectroscopic confirmations, derived from the parent sample presented by Shu et al. (2019), who applied a machine-learning approach to select QSO candidates from a combination of the Gaia DR2 and unWISE catalogs.  \nSimplified description of selection criteria: Starting with the Shu et al. (2019) catalog, select targets which satisfy the following criteria: i) have a Random Forest probability of being a QSO of > 0.8, ii) are in the magnitude range suitable for BOSS spectroscopy in dark time ( G dered > 16 . 5 and G RP, dered > 16 . 5, as well as G dered < 21 . 2 or G RP, dered < 21 . 0 Vega), and iii) do not have good optical spectroscopic measurements from a previous iteration of SDSS.  \nTarget priority options:  \n3400  \nCadence options:  \ndark 1x4  \nImplementation:  \nbhm gua.py  \nNumber of targets:  \n2156582  \nor c) the target is a secondary X-ray → optical/IR association. We assign cadences (exposure time requests) based on optical brightness.  \nTarget priority options:  \n1520-1523, 1720-1723  \nCadence options:  \nbright 2x1, dark 1x2, dark 1x4  \nImplementation:  \nbhm spiders agn.py  \nNumber of targets:  \n235745  \nB.18. bhm spiders agn ps1dr2  \ntarget selection plan:  \n0.5.0  \ntarget selection tag:  \n0.3.0  \nSummary: This is the second highest priority carton for SPIDERS AGN wide area follow up, included to expand the survey footprint beyond Legacy Survey DR8. The carton provides optical counterparts to point-like (unresolved) X-ray sources detected in early reductions of the first 6-months of eROSITA all sky survey data (eRASS:1). The sample is expected to contain a mixture of QSOs, AGN, stars and compact objects. The X-ray sources have been cross-matched by the eROSITA-DE team, first to CatWISE2020 mid-IR sources (Marocco et al. 2021), and then to optical counterparts from the PanSTARRS1 DR2 catalog. All targets are located in the sky hemisphere where MPE controls the data rights (approx. 180 < l < 360 deg), and at Dec > -30 deg, spanning a wide range of Galactic latitudes. Targets at low Galactic latitudes ( | b | < 15 deg) do not drive survey strategy.  \nSimplified description of selection criteria: Starting from a parent catalog of eRASS:1 point source → CatWISE2020 → PanSTARRS1 associations (method: NWAY assisted by IR priors computed via a pre-trained Random Forest, building on Salvato et al. 2022), select targets which meet all of the following criteria: i) have eROSITA detection likelihood > 6.0, ii) have an X-ray → IR cross-match probability of p any > 0.1, iii) have PanSTARRS1 g psf , r psf , i psf , z psf > 13 . 5 AB and at least one of PanSTARRS1 g psf < 22 . 5, r psf < 22 . 0, i psf < 21 . 5 or z psf < 20 . 5 AB, iv) are not associated with a bad PanSTARRS1 image stack, v) have non-null measurements of g psf , r psf and i psf , and vi) if detected by Gaia DR2 then have G > 13 . 5 and G RP > 13 . 5 Vega. We deprioritize targets if any of the following criteria are met: a) the target already has existing good quality SDSS spectroscopy, b) the X-ray detection likelihood is < 8.0, or c) the target is a secondary X-ray → IR association. We assign cadences (exposure time requests) based on optical brightness.  \nTarget priority options: 1530-1533,1730-1733,3530-3533,3730-3732  \nCadence options:  \nbright 2x1, dark 1x2, dark 1x4  \nImplementation:  \nbhm spiders agn.py  \nNumber of targets:  \n200681  \nB.19. bhm spiders agn gaiadr2  \ntarget selection plan:  \n0.5.0  \ntarget selection tag:  \n0.3.0  \nSummary: This is the third highest priority carton for SPIDERS AGN wide area follow up, included to expand the survey footprint to the full hemisphere where X-ray sources are available (beyond Legacy Survey DR8 and PanSTARRS1). The carton provides optical counterparts to point-like (unresolved) X-ray sources detected in early reductions of the first 6-months of eROSITA all sky survey data (eRASS:1). The sample is expected to contain a mixture of QSOs, AGN, stars and compact objects. The X-ray sources have been cross-matched by the eROSITA-DE team, first to CatWISE2020 mid-IR sources (Marocco et al. 2021), and then to optical counterparts from the Gaia-DR2 catalog. All targets are located in the sky hemisphere where MPE controls the data rights (approx. 180 < l < 360 deg). The targets in this carton distributed over a wide range of Galactic latitudes, but targets at low Galactic latitudes ( | b | < 15 deg) do not drive survey strategy.  \nSimplified description of selection criteria: Starting from a parent catalog of eRASS:1 point source → CatWISE2020 → Gaia DR2 associations (method: NWAY assisted by IR priors computed via a pre-trained Random Forest, building on Salvato et al. 2022), select targets which meet all of the following criteria: i) have eROSITA detection likelihood > 6.0, ii) have an X-ray → IR cross-match probability of p any > 0.1, and iii) have G > 13 . 5 and  \nG RP > 13 . 5 Vega. We deprioritize targets if any of the following criteria are met: a) the target already has existing good quality SDSS spectroscopy, b) the X-ray detection likelihood is < 8.0, or c) the target is a secondary X-ray → IR association. We assign cadences (exposure time requests) based on optical brightness.  \nTarget priority options: 1540-1543,1740-1743,3540-3543,3740-3742  \nCadence options:  \nbright 2x1, dark 1x2, dark 1x4  \nImplementation:  \nbhm spiders agn.py  \nNumber of targets:  \n324576  \nB.20. bhm spiders agn skymapperdr2  \ntarget selection plan:  \n0.5.0 0.3.0  \ntarget selection tag:  \nSummary: This is a lower ranked carton for SPIDERS AGN wide area follow up, which supplements the survey in areas that rely on Gaia DR2 (beyond Legacy Survey DR8 and PanSTARRS1) by recovering extended targets (galaxies) that are missed by Gaia. The carton provides optical counterparts to point-like (unresolved) X-ray sources detected in early reductions of the first 6-months of eROSITA all sky survey data (eRASS:1). The sample is expected to contain a mixture of QSOs, AGN, stars and compact objects. The X-ray sources have been cross-matched by the eROSITADE team, first to CatWISE2020 mid-IR sources (Marocco et al. 2021), and then to optical counterparts from the SkyMapper-DR2 catalog (Onken et al. 2019b). All targets are located in the sky hemisphere where MPE controls the data rights (approx. 180 < l < 360 deg) and at Dec < 0 deg, spanning a wide range of Galactic latitudes. Targets at low Galactic latitudes ( | b | < 15 deg) do not drive survey strategy.  \nSimplified description of selection criteria: Starting from a parent catalog of eRASS:1 point source → CatWISE2020 → SkyMapper-dr2 associations (method: NWAY assisted by IR priors computed via a pre-trained Random Forest, building on Salvato et al. 2022), select targets which meet all of the following criteria: i) have eROSITA detection likelihood > 6.0, ii) have an X-ray → IR cross-match probability of p any > 0.1, iii) have SkyMapper g psf , r psf , i psf , z psf > 13 . 5 AB and at least one of SkyMapper g psf < 22 . 5, r psf < 22 . 0, i psf < 21 . 5 or z psf < 20 . 5 AB, iv) are not associated with a bad SkyMapper source detection (flags < 4), v) have non-null measurements of g psf , r psf and i psf , and vi) if detected by Gaia DR2 then have G > 13 . 5 and G RP > 13 . 5 Vega. We deprioritize targets if any of the following criteria are met: a) the target already has existing good quality SDSS spectroscopy, b) the X-ray detection likelihood is < 8.0, or c) the target is a secondary X-ray → IR association. We assign cadences (exposure time requests) based on optical brightness.  \nTarget priority options:  \n1550-1553,1750-1753,3550-3553,3750-3752  \nCadence options:  \nbright 2x1, dark 1x2, dark 1x4  \nImplementation:  \nbhm spiders agn.py  \nNumber of targets:  \n82683  \nB.21. bhm spiders agn supercosmos  \ntarget selection plan:  \n0.5.0  \ntarget selection tag:  \n0.3.0  \nSummary: This is a lower ranked carton for SPIDERS AGN wide area follow up, which supplements the survey in areas which rely on Gaia-DR2 (beyond DESI Legacy Survey DR8 and PanSTARRS1) by recovering extended targets (galaxies) that are missed by Gaia. The carton provides optical counterparts to point-like (unresolved) X-ray sources detected in early reductions of the first 6-months of eROSITA all sky survey data (eRASS:1). The sample is expected to contain a mixture of QSOs, AGN, stars and compact objects. The X-ray sources have been cross-matched by the eROSITA-DE team, first to CatWISE2020 mid-IR sources (Marocco et al. 2021), and then to optical counterparts from the SuperCosmos Sky Surveys catalog (derived from scans of photographic plates). All targets are located in the sky hemisphere where MPE controls the data rights (approx. 180 < l < 360 deg), spanning a wide range of Galactic latitudes. Targets at low Galactic latitudes ( | b | < 15 deg) do not drive survey strategy.  \nSimplified description of selection criteria: Starting from a parent catalog of eRASS:1 point source → CatWISE2020 → SuperCosmos associations (method: NWAY assisted by IR priors computed via a pre-trained Random  \nForest, building on Salvato et al. 2022), select targets which meet all of the following criteria: i) have eROSITA detection likelihood > 6.0, ii) have an X-ray → IR cross-match probability of p any > 0.1, iii) have B J , psf , R psf , I psf > 13 . 5 Vega and at least one of B J , psf < 22 . 5, R psf < 22 . 0, or I psf < 21 . 5 Vega (photometry from SuperCosmos), and iv) if detected by Gaia DR2 then have G > 13 . 5 and G RP > 13 . 5 Vega. We deprioritize targets if any of the following criteria are met: a) the target already has existing good quality SDSS spectroscopy, b) the X-ray detection likelihood is < 8.0, or c) the target is a secondary X-ray → IR association. We assign cadences (exposure time requests) based on optical brightness.  \nTarget priority options:  \n1560-1563,1760-1763,3560-3563,3760-3763  \nCadence options:  \nbright 2x1, dark 1x2, dark 1x4  \nImplementation:  \nbhm spiders agn.py  \nNumber of targets:  \n430780  \nB.22. bhm spiders agn efeds stragglers  \ntarget selection plan:  \n0.5.0  \ntarget selection tag:  \n0.3.0  \nSummary: This is an opportunistic supplementary carton for SPIDERS AGN follow up, aiming, where fiber resources allow, to gather a small additional number of spectra for targets in the eFEDS field (which has been repeatedly surveyed in earlier iterations of SDSS). This carton provides optical counterparts to point-like (unresolved) X-ray sources detected in early reductions of the eROSITA/eFEDS performance validation field. The sample is expected to contain a mixture of QSOs, AGN, stars and compact objects. The X-ray sources have been cross-matched by the eROSITA-DE team to DESI Legacy Survey DR8 optical/IR counterparts. All targets in this carton are located within the eFEDS field (approx 126 < RA < 146, -3 < Dec < +6 deg). These targets do not drive survey strategy.  \nSimplified description of selection criteria: Starting from a parent catalog of eFEDS point source → legacysurvey.org/dr8 associations (method: NWAY assisted by optical/IR priors computed via a pre-trained Random Forest, see Salvato et al. 2022), select targets which meet all of the following criteria: i) have eROSITA detection likelihood > 6.0, ii) have an X-ray → optical/IR cross-match probability (NWAY) of p any > 0.1, iii) have 13 . 5 < r fibertot < 22 . 5 or 13 . 5 < z fibertot < 21 . 0 AB, iv) are not saturated in Legacy Survey imaging, v) have at least one observation in r -band and at least one observation in g - or z -band, and vi) if detected by Gaia DR2 then have G > 13 . 5 and G RP > 13 . 5 Vega. We deprioritize targets if any of the following criteria are met: a) the target already has existing good quality SDSS spectroscopy, b) the X-ray detection likelihood is < 8.0, or c) the target is a secondary X-ray → optical/IR association. We assign cadences (exposure time requests) based on optical brightness.  \nTarget priority options: 1510-1514, 1710-1714  \nCadence options:  \nbright 2x1, dark 1x2, dark 1x4  \nImplementation:  \nbhm spiders agn.py  \nNumber of targets:  \n15926  \nB.23. bhm spiders agn sep  \ntarget selection plan:  \n0.5.0  \ntarget selection tag:  \n0.3.0  \nSummary: This special carton is dedicated to SPIDERS AGN follow up in the CVZ-S/SEP field. The carton provides optical counterparts to point-like (unresolved) X-ray sources detected in a dedicated analysis of the first 6-months of eROSITA scanning data near the SEP. The X-ray sources have been cross-matched by the eROSITA-DE team, first to CatWISE2020 mid-IR sources (Marocco et al. 2021), and then to optical counterparts from the Gaia DR2 catalog, using additional filtering (including Gaia EDR3 astrometric information) to reduce the contamination from foreground stars located in the LMC. All targets are located within 1.5 deg of the South Ecliptic Pole (RA,Dec = 90.0,-66.56 deg). Simplified description of selection criteria: Starting from a parent catalog of eRASS:1/SEP point source → CatWISE2020 → Gaia DR2 associations (method: NWAY assisted by IR priors computed via a pre-trained Random Forest, building on Salvato et al. 2022), select targets which meet all of the following criteria: i) have eROSITA detection likelihood > 6.0, ii) have an X-ray → IR cross-match probability of p any > 0.1, and iii) have Gaia G > 13 . 5 and  \nG RP > 13 . 5 Vega. We deprioritize targets if any of the following criteria are met: a) the X-ray detection likelihood is < 8.0, or b) the target is a secondary X-ray → IR association. We assign cadences (exposure time requests) based on optical brightness.  \nTarget priority options:  \n1510,1512  \nCadence options:  \nbright 2x1, dark 1x2, dark 1x4  \nImplementation:  \nbhm spiders agn.py  \nNumber of targets:  \n697  \nB.24. bhm spiders clusters lsdr8  \ntarget selection plan:  \n0.5.0 0.3.0  \ntarget selection tag:  \nSummary: This is the highest priority carton for SPIDERS Clusters wide area follow up. The carton provides a list of galaxies which are candidate members of clusters selected from early reductions of the first 6-months of eROSITA all sky survey data (eRASS:1). The X-ray clusters have been associated by the eROSITA-DE team to DESI Legacy Survey DR8 (lsdr8) optical/IR counterparts using the eROMaPPeR red-sequence finder algorithm (Rykoff et al. 2014; Ider Chitham et al. 2020). All targets are located in the sky hemisphere where MPE controls the data rights (approx. 180 < l < 360 deg). Due to the footprint of lsdr8, nearly all targets in this carton are located at high Galactic latitudes ( | b | > 15 deg).  \nSimplified description of selection criteria: Starting from a parent catalog of eRASS:1 → lsdr8 eROMaPPeR cluster associations, select targets which meet all of the following criteria: i) have 13 . 5 < r fibertot < 21 . 0 or 13 . 5 < z fibertot < 20 . 0 AB, ii) if detected by Gaia DR2 then have G > 13 . 5 and G RP > 13 . 5 Vega (photometry from lsdr8), and iii) do not have existing good quality SDSS spectroscopy. We assign a range of priorities to targets in this carton, with BCGs top ranked, followed by candidate member galaxies according their probability of membership. We assign cadences (exposure time requests) based on optical brightness.  \nTarget priority options: 1501,1630-1659  \nCadence options:  \nbright 2x1, dark 1x2, dark 1x4  \nImplementation:  \nbhm spiders clusters.py  \nNumber of targets:  \n87490  \nB.25. bhm spiders clusters ps1dr2  \ntarget selection plan:  \n0.5.0  \ntarget selection tag:  \n0.3.0  \nSummary: This is the second highest priority carton for SPIDERS Clusters wide area follow up, designed to expand the survey area beyond the Legacy Survey DR8 footprint. The carton provides a list of galaxies that are candidate members of clusters selected from early reductions of the first 6-months of eROSITA all sky survey data (eRASS:1). The X-ray clusters have been associated by the eROSITA-DE team to the PanSTARRS1-DR2 catalog using the eROMaPPeR red-sequence finder algorithm (Rykoff et al. 2014; Ider Chitham et al. 2020). All targets are located in the sky hemisphere where MPE controls the data rights (approx. 180 < l < 360 deg). Nearly all targets in this carton are located at high Galactic latitudes ( | b | > 15 deg).  \nSimplified description of selection criteria: Starting from a parent catalog of eRASS:1 → PanSTARRS1-DR2 eROMaPPeR cluster associations, select targets which meet all of the following criteria: i) have PanSTARRS1 r psf , i psf , z psf > 13 . 5 AB and at least one of r psf < 21 . 5, i psf < 21 . 0 or z psf < 20 . 5 AB, and ii) do not have existing good quality SDSS spectroscopy. We assign a range of priorities to targets in this carton, with BCGs top ranked, followed by candidate member galaxies according their probability of membership. We assign cadences (exposure time requests) based on optical brightness.  \nTarget priority options: 1502,1660-1689  \nCadence options:  \nbright 2x1,dark 1x2,dark 1x4  \nImplementation:  \nbhm spiders clusters.py  \nNumber of targets:  \n86179  \nB.26. bhm spiders clusters efeds stragglers  \ntarget selection plan:  \n0.5.0 0.3.0  \ntarget selection tag:  \nSummary: This is an opportunistic supplementary carton for SPIDERS Clusters follow up, aiming, where fiber resources allow, to gather a small additional number of spectra for targets in the eFEDS field (which has been repeatedly surveyed in earlier iterations of SDSS). The carton provides a list of galaxies which are candidate members of clusters selected from early reductions of the eROSITA performance verification survey in the eFEDS field. The X-ray clusters have been associated by the eROSITA-DE team to DESI Legacy Survey DR8 (lsdr8) optical/IR counterparts. All targets in this carton are located within the eFEDS field (approx 126 < RA < 146, -3 < Dec < +6 deg).  \nSimplified description of selection criteria: Starting from a parent catalog of eFEDS → legacysurvey.org/dr8 cluster associations (eROMaPPeR, Rykoff et al. 2014; Ider Chitham et al. 2020; Liu et al. 2022), select targets which meet all of the following criteria: have 13 . 5 < r fibertot < 21 . 0 or 13 . 5 < z fibertot < 20 . 0 AB, ii) if detected by Gaia DR2 then have G > 13 . 5 and G RP > 13 . 5 Vega (photometry from lsdr8), and iii) do not have existing good quality SDSS spectroscopy. We assign a range of priorities to targets in this carton, with BCGs top ranked, followed by candidate member galaxies according their probability of membership. We assign cadences (exposure time requests) based on optical brightness.  \nTarget priority options:  \n1500,1600-1629  \nCadence options:  \ndark 1x2,dark 1x4  \nImplementation:  \nbhm spiders clusters.py  \nNumber of targets:  \n3060  \nB.27. bhm spiders agn-efeds  \ntarget selection plan:  \n0.1.0  \ntarget selection tag:  \n0.1.0  \nSummary: A carton used during SDSS-V plate-mode observations that contains candidate AGN targets found in the eROSITA/eFEDS X-ray survey field. This carton provides optical counterparts to point-like (unresolved) X-ray sources detected in early reductions ('c940/V2T') of the eROSITA/eFEDS performance validation field. The sample is expected to contain a mixture of QSOs, AGN, stars and compact objects. The X-ray sources have been cross-matched by the eROSITA-DE team to DESI Legacy Survey DR8 (lsdr8) optical/IR counterparts. All targets in this carton are located within the eFEDS field (approx 126 < RA < 146, -3 < Dec < +6 deg).  \nSimplified description of selection criteria: Starting from a parent catalog of eFEDS point source → lsdr8 associations (primarily via NWAY assisted by optical/IR priors computed via a pre-trained Random Forest, see Salvato et al. 2022, supplemented by counterparts selected via a Likelihood Ratio using r -band magnitudes), select targets which meet all of the following criteria: i) have eROSITA detection likelihood > 6.0, ii) have an X-ray → optical/IR cross-match probability of either p any > 0.1 (NWAY associations) or LR > 0.2 (Likelihood Ratio associations), iii) have r fiber > 16 . 5 and either r fiber < 22 . 0 or z fiber < 21 . 0 AB (photometry from lsdr8), and iv) did not receive high quality spectroscopy during the SDSS-IV observations of the eFEDS field (Abdurro'uf et al. 2022). We deprioritize targets if any of the following criteria are met: a) the target already has existing good quality SDSS spectroscopy in SDSS DR16, b) the X-ray detection likelihood is < 8.0, c) the target is a secondary X-ray → optical/IR association, or d) the optical/IR counterpart was only chosen by the LR method. All targets were assigned a nominal cadence of: bhm spiders 1x8 (8x15mins dark time).  \nTarget priority options:  \n1510-1519  \nCadence options:  \nbhm spiders 1x8  \nImplementation:  \nbhm spiders agn.py  \nNumber of targets:  \n12459  \nB.28. bhm spiders clusters-efeds-ls-redmapper", 'target selection tag: 0.1.0': "Summary: A carton used during SDSS-V plate-mode observations that contains galaxy cluster targets found in the eROSITA/eFEDS X-ray survey field. The carton provides a list of galaxies which are candidate members of clusters selected from early reductions ('c940') of the eROSITA performance verification survey in the eFEDS field. The parent sample of galaxy clusters and their member galaxies have been selected via a joint analysis of X-ray and (several) optical/IR datasets using the eROMaPPeR red-sequence finder algorithm (Rykoff et al. 2014; Ider Chitham et al. 2020). This particular carton relies on optical/IR data from DESI Legacy Survey DR8 (lsdr8). All targets in this carton are located within the eFEDS field (approx 126 < RA < 146, -3 < Dec < +6 deg).  \nSimplified description of selection criteria: Starting from a parent catalog of eFEDS → optical/IR cluster associations, select targets which meet all of the following criteria: i) are selected by eROMaPPeR applied to lsdr8 photometric data, ii) have eROSITA X-ray detection likelihood > 8.0, iii) have r fiber > 16 . 5 and either r fiber < 21 . 0 or z fiber < 20 . 0 AB (photometry from lsdr8), and iv) do not have existing good quality (SDSS or external) spectroscopy. We assign a range of priorities to targets in this carton, with BCGs top ranked, followed by candidate member galaxies according their probability of membership. All targets were assigned a nominal cadence of: bhm spiders 1x8 (8x15mins dark time).  \nTarget priority options:  \n1500, 1511--1610  \nCadence options:  \ndark 1x8  \nImplementation:  \nbhm spiders clusters.py  \nNumber of targets:  \n4432  \nB.29. bhm spiders clusters-efeds-sdss-redmapper  \ntarget selection plan:  \n0.1.0 0.1.0  \ntarget selection tag:  \nSummary: A carton used during SDSS-V plate-mode observations that contains galaxy cluster targets found in the eROSITA/eFEDS X-ray survey field. The carton provides a list of galaxies which are candidate members of clusters selected from early reductions ('c940') of the eROSITA performance verification survey in the eFEDS field. The parent sample of galaxy clusters and their member galaxies have been selected via a joint analysis of X-ray and (several) optical/IR datasets using the eROMaPPeR red-sequence finder algorithm (Rykoff et al. 2014; Ider Chitham et al. 2020). This particular carton relies on optical photometric data from SDSS DR13. All targets in this carton are located within the eFEDS field (approx 126 < RA < 146, -3 < Dec < +6 deg).  \nSimplified description of selection criteria: Starting from a parent catalog of eFEDS → optical/IR cluster associations, select targets which meet all of the following criteria: i) are selected by eROMaPPeR applied to SDSS dr13 photometric data, ii) have eROSITA X-ray detection likelihood > 8.0, iii) have r fiber > 16 . 5 and either r fiber < 21 . 0 or z fiber < 20 . 0 AB (photometry from DESI Legacy Survey DR8), and iv) do not have existing good quality (SDSS or external) spectroscopy. We assign a range of priorities to targets in this carton, with BCGs top ranked, followed by candidate member galaxies according their probability of membership. All targets were assigned a nominal cadence of: bhm spiders 1x8 (8x15mins dark time).  \nTarget priority options:  \n1500, 1511-1610  \nCadence options:  \ndark 1x8  \nImplementation:  \nbhm spiders clusters.py  \nNumber of targets:  \n4304  \nB.30. bhm spiders clusters-efeds-hsc-redmapper  \ntarget selection plan:  \n0.1.0  \ntarget selection tag:  \n0.1.0  \nSummary: A carton used during SDSS-V plate-mode observations that contains galaxy cluster targets found in the eROSITA/eFEDS X-ray survey field. The carton provides a list of galaxies which are candidate members of clusters selected from early reductions ('c940') of the eROSITA performance verification survey in the eFEDS field. The parent sample of galaxy clusters and their member galaxies have been selected via a joint analysis of X-ray and  \n(several) optical/IR datasets using the eROMaPPeR red-sequence finder algorithm (Rykoff et al. 2014; Ider Chitham et al. 2020). This particular carton relies on optical/IR data from the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP). All targets in this carton are located within the eFEDS field (approx 126 < RA < 146, -3 < Dec < +6 deg). Simplified description of selection criteria: Starting from a parent catalog of eFEDS → optical/IR cluster associations, select targets which meet all of the following criteria: i) are selected by eROMaPPeR applied to HSCSSP photometric data, ii) have eROSITA X-ray detection likelihood > 8.0, iii) have r fiber > 16 . 5 and either r fiber < 21 . 0 or z fiber < 20 . 0 AB (photometry from DESI Legacy Survey DR8), and iv) do not have existing good quality (SDSS or external) spectroscopy. We assign a range of priorities to targets in this carton, with BCGs top ranked, followed by candidate member galaxies according their probability of membership. All targets were assigned a nominal cadence of: bhm spiders 1x8 (8x15mins dark time).  \nTarget priority options: 1500, 1511-1610  \nCadence options:  \ndark 1x8  \nImplementation:  \nbhm spiders clusters.py  \nNumber of targets:  \n924  \nB.31. bhm spiders clusters-efeds-erosita  \ntarget selection plan:  \n0.1.0 0.1.0  \ntarget selection tag:  \nSummary: A carton used during SDSS-V plate-mode observations that contains galaxy cluster targets found in the eROSITA/eFEDS X-ray survey field. The carton provides a list of galaxies which are candidate members of clusters selected from early reductions ('c940') of the eROSITA performance verification survey in the eFEDS field. The parent sample of galaxy clusters and their member galaxies have been selected via a joint analysis of X-ray and (several) optical/IR datasets. This particular carton includes counterparts to X-ray extended sources that were not selected by the eROMaPPeR red sequence finder algorithm when applied to any of the DESI Legacy Survey DR8, SDSS DR13, or HSC-SSP datasets (i.e., complementary to the cartons: bhm spiders clusters-efeds-ls-redmapper, bhm spiders clustersefeds-sdss-redmapper and bhm spiders clusters-efeds-hsc-redmapper). All targets in this carton are located within the eFEDS field (approx 126 < RA < 146, -3 < Dec < +6 deg).  \nSimplified description of selection criteria: Starting from a parent catalog of eFEDS → optical/IR cluster associations, select targets which meet all of the following criteria: i) are identified as being X-ray extended but not selected via the eROMaPPeR algorithm, ii) have eROSITA X-ray detection likelihood > 8.0, iii) have r fiber > 16 . 5 and either r fiber < 21 . 0 or z fiber < 20 . 0 AB (photometry from DESI Legacy Survey DR8), and iv) do not have existing good quality (SDSS or external) spectroscopy. We assign a range of priorities to targets in this carton, with BCGs top ranked, followed by candidate member galaxies according their probability of membership. All targets were assigned a nominal cadence of: bhm spiders 1x8 (8x15mins dark time).  \nTarget priority options:  \n1500, 1511-1535  \nCadence options:  \ndark 1x8  \nImplementation:  \nbhm spiders clusters.py  \nNumber of targets:  \n15"}