The Eighteenth Data Release of the Sloan Digital Sky Surveys: Targeting and First Spectra from SDSS-V

Previous generations of SDSS relied almost exclusively on a single imaging catalog for targeting. In the optical, the SDSS imaging survey (Padmanabhan et al. 2008; Abazajian et al. 2009) formed the basis for targeting, while in the H band, the Two Micron All Sky Survey (2MASS) 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 IR. Gaia imaging does not go deep enough in the extragalactic sky, while even the union of SDSS imaging, Pan-STARRS imaging, and other wide-field imaging does not cover the full sky at the necessary wavelengths.

Therefore, 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 MOS targets (i.e., all targets for MWM and BHM) 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; Section 5.2 describes how the targeting classifications are stored.

Figure 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 crossmatched 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.

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The 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 crossmatched 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 crossmatched 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).

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The initial basis for mos_catalog is the TESS Input Catalog (TIC) v8 (Stassun et al. 2019), which is all-sky and uses both Gaia DR2 and 2MASS to identify objects. ⁹³ Then, crossmatching 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 crossmatches 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.

For 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'' search radius, but this value is sometimes modified to match the spatial resolution of the input catalog. All the cone-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 ⁹⁴ by setting the best column in the mos_catalog_to_X table to True. Finally, targets in the input catalog that cannot be spatially crossmatched are considered new physical objects and added to mos_catalog and mos_catalog_to_X with a new unique catalogid.

For some of these 17 catalogs, the database contains further associations between them and the additional catalogs used in targeting. Figure 3 shows these other catalogs and how they are associated in the database with the crossmatched catalogs.

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DR18 contains the catalog crossmatching 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 have not yet been made public. Due to an error, DR18 also excludes tables associated with the TESS Objects of Interest (TOIs), 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.

Drawing on the catalog database and the information stored in the linked catalogs described above (Section 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.

After 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.

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For example, consider a star that has a detection in Gaia DR2. This star will appear in 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.

Each 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 the fiber assignment process. The cadence describes how the target should be observed (number of epochs, number of observations per epoch, and observing conditions). The cadence_pk values allow a join to a cadence table with the cadence name and other parameters associated with it.

The 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 (M. R. Blanton et al. 2023, in preparation).

Each 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 (Sections 5.3–5.4).

Among the science target cartons, there are those whose observations are required for the stated success of 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.

5.3.1. APOGEE Standard Stars

5.3.2. BOSS Spectrophotometric Standard Stars

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.

With 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.

First, the sky is divided into HEALPix NSIDE = 32 pixel "tiles," comprising roughly 3.4 deg² pix⁻¹, which is approximately the area spanned by a single FPS configuration. Each tile is further divided into HEALpix NSIDE = 32,768 pixels (41 arcsec² pix⁻¹), the centers of which are considered candidate sky locations. ⁹⁵ Each candidate 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 = 32,768 HEALpixel contains no astrophysical objects in that catalog, and (ii) they lie farther than a magnitude-dependent separation from the nearest potentially contaminating astrophysical source. This minimum separation is computed as ${s}^{* }=s+\tfrac{{({m}_{\mathrm{thr}}-m)}^{\beta }}{a}$, where s = 5'' 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 (Høg et al. 2000; Skrutskie et al. 2006; Gaia Collaboration et al. 2018; Dey et al. 2019; Flewelling et al. 2020). 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.

The 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 farthest 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.

For 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 lower-priority ops_sky_apogee_good carton is dedicated to finding the remaining least-bad sky locations in dense regions. These positions have a maximum nearest neighbor brightness of H = 10, and candidates lying farthest from 2MASS contaminants are preferred.

Galactic Genesis (GG) is the flagship program of MWM, with near-IR (APOGEE) observations of over four million stars planned. GG's central science goal is 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, GG targets luminous red giants, above the red clump, where the multimillion sample size with dust-penetrating APOGEE observations provides a decisive advantage over other surveys.

All of the GG targets are contained in the mwm_galactic_core carton.

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 binary WD merging channels toward type Ia supernovae and other remnant products (e.g., Chandra et al. 2021).

All of the MWM WDs targeted for this program are contained in the mwm_wd_core carton.

MWM's Solar Neighborhood Census (SNC) program targets a volume-limited sample of stars with the goal of cataloging low-luminosity stellar populations. While not technically "complete," the SNC will provide high-quality, two-epoch BOSS or APOGEE spectra of >10⁵ 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.

The SNC targets span four cartons, all beginning with mwm_snc: mwm_snc_100pc_apogee, mwm_snc_100pc_boss, mwm_snc_250pc_apogee, and mwm_snc_250pc_boss, where the latter part of the carton names indicate the volume size and instrument.

The MWM YSO program targets the pre-main-sequence 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 spectral energy distribution, or variability. APOGEE spectra then provide stellar parameters and velocities, while BOSS spectra provide indicators of youth, such as Li absorption and Hα emission. Kounkel et al. (submitted) present a complete discussion of the target selection rationale and on-sky validation.

Cartons 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.

Massive stars on the main sequence are unambiguously young because of their short hydrogen burning lifetimes. 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 BHs and NSs, objects that were once even more massive stars. These hot stars are also the dominant ionizers of the ISM. The MWM OB program targets all stars brighter than G = 16 that are also likely to be hotter than ∼8000 K.

The 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 Milky Way and Magellanic Clouds.

In addition to the spectroscopic follow-up of high-redshift X-ray sources from eROSITA (Section 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.

The 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.

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 program uses asteroseismic and photometric data to identify the likeliest double-lined spectroscopic EBs with pulsational variability, among OBA stellar types.

These targets are contained in the manual_mwm_tess_ob carton.

The APOGEE-1 and APOGEE-2 surveys contributed to binary studies both through statistical studies of large samples (e.g., Mazzola et al. 2020; Price-Whelan 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 GG criteria (see above). The Binary Systems program is further enhancing this sample of stellar and substellar companions of stars across the H-R diagram by investing fibers to extend the time baselines of red giants, subgiants, and M dwarfs. This program exclusively uses the APOGEE spectrograph because of its superior spectral resolution and improved radial velocity precision.

Targets in this program fall into 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.

Spectra of compact binary systems are frequently marked by nonstellar emission—such as X-ray, UV, or Hα 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). ⁹⁷

These 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.

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 TOIs. These will be observed with the APOGEE instrument to provide stellar parameters and detailed stellar abundances.

The single carton in this program is called mwm_tess_planet.

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 with 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.

The single carton in this program is called mwm_tessrgb_core.

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, as well as valuable information on the 3D structure of the cold ISM. MWM's Dust program is obtaining spectra for mapping distributions of the density and properties of dust (such as R_V ; e.g., Schlafly et al. 2016). Those spectra will 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 GG program, to achieve an even sampling of the Milky Way's dust with the total MWM sample.

The single carton in this program is called mwm_dust_core.

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 APOGEE-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.

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 timescales. SDSS-V studies black hole masses via RM, possible SMBH binarity, time-resolved accretion events, broad-line region (BLR) dynamics, and broad absorption line quasi-stellar object outflows. The SDSS-V quasar time-domain programs build on the results and experience of earlier generations of SDSS, e.g., the SDSS-III/IV RM project (Shen et al. 2015) and the Time Domain Spectroscopic Survey (MacLeod et al. 2018), to enable long time baselines.

7.1.1. All-quasar Multi-epoch Spectroscopy

7.1.2. RM

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 (Section 7.2.1) and a substantial complementary program following up Chandra archival X-ray source catalogs (Section 7.2.2).

7.2.1. Spectroscopic Identification of eROSITA Sources

7.2.2. Chandra Source Catalog

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 deg² 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 pointlike and extended X-ray sources (Klein et al. 2022; Salvato et al. 2022). From past experience (e.g., Clerc et al. 2016, 2020; Menzel et al. 2016; LaMassa et al. 2019), one can expect these X-ray populations to be numerically dominated by AGNs and clusters of galaxies, but we also expect a substantial minority to be associated with stellar coronal emitters or accreting compact objects.

Below, we give a summary of the observational goals, target selection, and survey strategy for the SDSS-V/eFEDS observations. Details of the plate design and the scope and quality of the observed data set can be found in Section 9.1.

7.3.1. SDSS-V/eFEDS Observational Goals

7.3.2. Target Selection for SDSS-V/eFEDS Plates

The scientific objectives and carton design of the eFEDS program can be found in Section 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 APO using the existing fiber plug plate 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 (K. Covey et al. 2023, in preparation). Here, we provide a summary of the special considerations that apply specifically to the SDSS-V/eFEDS plates.

Each 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 (Section 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; Section 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 a shift in priority of a carton with respect to another or an update to 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.

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SDSS-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 deg² 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, resulted 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.

For 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. ¹⁰¹ 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 crosstalk between neighboring BOSS fiber traces.

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9.1.2. Spectroscopic Observations, Reductions, and Data Quality

9.1.3. Accessing eFEDS Data

Users of DR18 may come across science spectra (i.e., not standard stars or sky targets) that were included in the eFEDS plates (Section 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:

• 1.  
  mwm_cb_cvcandidates
• 2.  
  mwm_cb_gaiagalex
• 3.  
  mwm_cb_uvex1
• 4.  
  mwm_cb_uvex2
• 5.  
  mwm_cb_uvex3
• 6.  
  mwm_cb_uvex4
• 7.  
  mwm_cb_uvex5
• 8.  
  mwm_halo_bb
• 9.  
  mwm_halo_sm
• 10.  
  mwm_snc_100pc
• 11.  
  mwm_wd

Users can expect improved and vetted versions of these spectra in DR19.

The optical BOSS data released in DR18 (Section 9.1) are processed with version v6_0_4 of the BOSS pipeline software idlspec2d (Bolton et al. 2012; Dawson et al. 2013; S. Morrison et al. 2023, in preparation). 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.

One of the most significant operational changes to the pipeline is a modification to reduce 500 fibers from a single 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.

A number of smaller changes were implemented into the pipeline to both improve the 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 4σ to 50σ. This change, in some rare cases, might leave the remnant of a cosmic ray in the extracted spectra.

Second, we modified the coadding scheme of targets between exposure frames and the red/blue cameras; individual spectra are now grouped according to the R.A., decl. 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 S/N of the final reduced spectra.

Third, v6_0_4 was modified to produce a special version of the DR18 SDSS-V/eFEDS spectra (Section 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 S/N. Both the standard pipeline, v6_0_4, and the eFEDS special coadds are available through the SAS ¹⁰³ and the CAS, using SkyServer. ¹⁰⁴ Future data releases will include variations of this special coadding routine, with the spectra included in each coadd chosen to fulfill the science requirements of the individual SDSS-V science programs.

Fourth, 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 principal component analysis (PCA) templates are used for PCA reconstruction and the redshift estimation of SDSS-V quasars. These new PCA templates are implemented with 10 eigenvectors instead of the four 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 Schlegel et al. (1998) model for dust extinction (see also 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 (Tonry & Davis 1979; Kurtz et al. 1992; Mink & Kurtz 1998), was added as part of the spec1d analysis pipeline for cross-correlating a spectrum against template spectra of known velocities. While this step is run for all targets, the results are only valid for stellar targets.

Finally, idlspec2d's internal Python dependencies were updated to Python3, with the deprecation of Python 2.7. All of the changes described here improve either the data quality or spectroscopic classification success rates, or support the changes to the BOSS spectrograph for the SDSS-V plate program and FPS observations.

For SDSS-V, all of the SDSS software has been moved to a GitHub organization, ¹⁰⁵ 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.

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 spectra (Section 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 Sánchez-Gallego et al. (2020).

Combining 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 a 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 completions.

One major challenge of the SDSS robotic fiber positioner system derives from the fact that the patrol radius of each positioner overlaps with its neighboring ones. 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 lattice-like 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).

Table 6 includes the following VACs that rely on SDSS-IV data but have been updated or published for the first time after DR17:

BACCHUS 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-S/N giants from APOGEE DR17, for which Na, P, S, V, Cu, Ce, and Nd abundances and ¹²C/¹³C isotopic ratios have been derived with a specialized analysis (Hayes et al. 2022). An updated version of the Brussels Automatic Code for Characterizing High accUracy Spectra (BACCHUS; 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 physics to Galactic chemical evolution and Milky Way population studies.

MaNGA Dwarf Galaxy Sample (MaNDala). This VAC presents properties for a sample of 125 dwarf galaxies (M_⋆ < 10⁹ M_⊙) observed with MaNGA (Cano-Díaz et al. 2022), including newly derived photometric results, such as surface brightness, color, and position angle. Also measured are photometric profiles, along with Sérsic 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_⋆, star formation rates, metallicities, ages, and other properties, using MaNGA Pipe3D data products (Sánchez et al. 2016, 2018). Details of the MaNDala sample and analysis are given in Cano-Díaz et al. (2022).

MaNGA Visual Morphology. This is an update of a VAC, originally released in DR17 (Section 5.5.2 in Abdurro'uf et al. 2022), which contains visual morphological classifications for MaNGA galaxies based on SDSS and DECaLs (Dey et al. 2019) images. See Vázquez-Mata et al. (2022) for details.

The only VAC in DR18 derived from SDSS-V data is that providing supplementary properties for the eFEDS spectroscopic data set (Section 7.3).

This 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 redshifts 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 Section 9.1. We combine automated redshifts and classifications, derived from the BOSS idlspec1d pipeline (Section 10.1), with an extensive set of visual inspections, which together increase the reliability and completeness of the spectroscopic coverage.

The VAC includes three separate catalogs:

• 1.  
  eFEDS_Main_speccomp—an update of redshift and classification information for the eFEDS Main (0.2–2.3 keV selection) source counterparts catalog;
• 2.  
  eFEDS_Hard_speccomp—an update of redshift and classification information for the eFEDS Hard-band (2.3–5 keV selection) source counterparts catalog; and
• 3.  
  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.

A full description of this VAC will be provided in A. Merloni et al. (2023, in preparation).

• Description of selection criteria: a system selected from the Ijspeert et al. (2021) catalog of massive EBs in TESS. The systems chosen were in the TESS continuous viewing zones (CVZs) and had TESS lightcurves that show pronounced eclipses and intrinsic variability.
• Data sources: Ijspeert et al. (2021).
• Target priority options: 2200.
• Cadence options: bright_8x1, bright_8x2, bright_8x4.

• 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.
• Data sources: 2MASS PSC (H), Gaia DR2 (G).
• Target priority options: 1400.
• Cadence options: bright_1x1.

• 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.
• Data sources: 2MASS PSC (H), Gaia DR2 (G).
• Target priority options: 1400.
• Cadence options: bright_1x1, dark_1x2.

• Description of selection criteria: bright compact binary candidates within 300 pc.

  • 1.  
    $({FUV}-5{\mathrm{log}}_{10}({r}_{\mathrm{est}}/10))\gt 14({FUV}-{NUV})-46;$
  • 2.  
    r_est < 300 pc;
  • 3.  
    H < 11.
• Data sources: Bailer-Jones et al. (2018) distance catalog (r_est), 2MASS PSC (H), GALEX (FUV, NUV).
• Target priority options: 1400.
• Cadence options: bright_1x1.

• Description of selection criteria: faint compact binary candidates within 300 pc.

  • 1.  
    $({FUV}-5{\mathrm{log}}_{10}({r}_{\mathrm{est}}/10))\gt 14({FUV}-{NUV})-46;$
  • 2.  
    r_est < 300 pc.
• Data sources: Bailer-Jones et al. (2018) distance catalog (r_est), GALEX (FUV, NUV).
• Target priority options: 1400.
• Cadence options: bright_2x1, dark_2x1.

• Description of selection criteria: bright AAVSO cataclysmic variables.

  • 1.  
    Target in mos_cataclysmic_variables table;
  • 2.  
    H < 11.
• Data sources: 2MASS PSC (H).
• Target priority options: 1400.
• Cadence options: bright_1x1.

• Description of selection criteria: faint AAVSO cataclysmic variables.

  • 1.  
    Target in mos_cataclysmic_variables table;
  • 2.  
    H ≥ 11.
• Data sources: 2MASS PSC (H).
• Target priority options: 1400.
• Cadence options: bright_2x1, dark_2x1.

• Description of selection criteria: bright compact binary candidates using Gaia G and GALEX FUV color cut.

  • 1.  
    ϖ/σ_ϖ > 3;
  • 2.  
    G < 20;
  • 3.  
    ${FUV}+5\mathrm{log}{1}_{10}(\varpi /1000)+5\,\gt \,1.5\,+\,1.28({FUV}\,-\,G);$
  • 4.  
    H < 11.
• Data sources: Gaia DR2 (G, ϖ, σ_ϖ ), 2MASS PSC (H), GALEX (FUV).
• Target priority options: 1400.
• Cadence options: bright_1x1.

• Description of selection criteria: faint compact binary candidates using Gaia G and GALEX FUV color cut.

  • 1.  
    ϖ/σ_ϖ > 3;
  • 2.  
    G < 20;
  • 3.  
    ${FUV}+5{\mathrm{log}}_{10}(\varpi /1000)+5\gt 1.5+1.28({FUV}-G);$
  • 4.  
    H ≥ 11.
• Data sources: Gaia DR2 (G, ϖ, σ_ϖ ), 2MASS PSC (H), GALEX (FUV).
• Target priority options: 1400.
• Cadence options: bright_2x1, dark_2x1.

• Description of selection criteria: Gaia and GALEX crossmatch, 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 the Gaia absolute magnitude calculated with r_est.

  • 1.  
    r_lo ≤ 1500;
  • 2.  
    g_vis_per >5;
  • 3.  
    Neither of the following two conditions are met:

    • (a)  
      $({\mathrm{log}}_{10}(\mu /{\sigma }_{\mu })\lt 0.301)$ AND $(\varpi /{\sigma }_{\varpi }\gt -1.4996{\mathrm{log}}_{10}(\mu /{\sigma }_{\mu })-4.05)$ AND $(\varpi /{\sigma }_{\varpi }\lt 1.4995{\mathrm{log}}_{10}(\mu /{\sigma }_{\mu })+4.05);$
    • (b)  
      ${({\mathrm{log}}_{10}{(\mu /{\sigma }_{\mu })-0.301)}^{2}/{0.39794}^{2}+(\varpi /{\sigma }_{\varpi })}^{2}/{4.5}^{2}\leqslant 1;$
  • 4.  
    NUV > − 100;
  • 5.  
    FUV > − 100;
  • 6.  
    σ_NUV < 0.2;
  • 7.  
    σ_FUV < 0.2;
  • 8.  
    M_G > 4.09 OR M_G > 4.5457(G_BP − G_RP) + 4.0457;
  • 9.  
    M_G > − 1.11749253 × 10⁻³(FUV − NUV)³ + 1.53748615 × 10⁻²(FUV − NUV)² + 3.66419895 × 10⁻¹(FUV − NUV) + 2.20026639);
  • 10.  
    (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)].
• Data 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).
• Target priority options: 1400.
• Cadence options: bright_1x1, dark_1x2, dark_1x3.

• Description of selection criteria: Gaia and GALEX crossmatch, 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.

  • 1.  
    r_lo ≤ 1500;
  • 2.  
    g_vis_per >5;
  • 3.  
    Neither of the following two conditions are met:

    • (a)  
      $({\mathrm{log}}_{10}(\mu /{\sigma }_{\mu })\lt 0.301)$ AND $(\varpi /{\sigma }_{\varpi }\gt -1.4996{\mathrm{log}}_{10}(\mu /{\sigma }_{\mu })-4.05)$ AND $(\varpi /{\sigma }_{\varpi }\lt 1.4995{\mathrm{log}}_{10}(\mu /{\sigma }_{\mu })+4.05);$
    • (b)  
      ${({\mathrm{log}}_{10}{(\mu /{\sigma }_{\mu })-0.301)}^{2}/{0.39794}^{2}+(\varpi /{\sigma }_{\varpi })}^{2}/{4.5}^{2}\leqslant 1;$
  • 4.  
    NUV > − 100;
  • 5.  
    σ_NUV < 0.2;
  • 6.  
    M_G > 4.09 OR M_G > 4.5457(G_BP − G_RP) + 4.0457;
  • 7.  
    (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)].
• Data 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).
• Target priority options: 1400.
• Cadence options: bright_1x1, dark_1x2, dark_1x3.

• Description of selection criteria: Gaia and XMM-Newton Optical Monitor SUSS Catalog crossmatch, keeping the nearest match within 3'' and removing objects with small proper motion and parallax. Color and quality cuts utilize the XMM UVM2 band.

  • 1.  
    r_lo ≤ 1500;
  • 2.  
    g_vis_per >5;
  • 3.  
    Neither of the following two conditions are met:

    • (a)  
      $({\mathrm{log}}_{10}(\mu /{\sigma }_{\mu })\lt 0.301)$ AND $(\varpi /{\sigma }_{\varpi }\gt -1.4996{\mathrm{log}}_{10}(\mu /{\sigma }_{\mu })-4.05)$ AND $(\varpi /{\sigma }_{\varpi }\lt 1.4995{\mathrm{log}}_{10}(\mu /{\sigma }_{\mu })+4.05);$
    • (b)  
      ${({\mathrm{log}}_{10}{(\mu /{\sigma }_{\mu })-0.301)}^{2}/{0.39794}^{2}+(\varpi /{\sigma }_{\varpi })}^{2}/{4.5}^{2}\leqslant 1;$
  • 4.  
    The following conditions are all NOT met:

    • (a)  
      qflag bit 1, 7, 8, or 9 is set;
    • (b)  
      qflag bit 2 or 3 is set AND UVM2 _signif < 10;
  • 5.  
    M_G > 4.09 OR M_G > 4.5457(G_BP − G_RP) + 4.0457;
  • 6.  
    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)].
• Data 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).
• Target priority options: 1400.
• Cadence options: bright_1x1, dark_1x2, dark_1x3.

• Description of selection criteria: Gaia and Swift UVOT Catalog crossmatch, keeping the nearest match within 3'' and removing objects with small proper motion and parallax. Color cuts utilize the UVW2 band, and quality cuts utilize both UVW2 and UVW1.

  • 1.  
    r_lo ≤ 1500;
  • 2.  
    g_vis_per >5;
  • 3.  
    UVW1_AB > −100;
  • 4.  
    UVW2_AB > −100;
  • 5.  
    Neither of the following two conditions are met:

    • (a)  
      $({\mathrm{log}}_{10}(\mu /{\sigma }_{\mu })\lt 0.301)$ AND $(\varpi /{\sigma }_{\varpi }\gt -1.4996{\mathrm{log}}_{10}(\mu /{\sigma }_{\mu })-4.05)$ AND $(\varpi /{\sigma }_{\varpi }\lt 1.4995{\mathrm{log}}_{10}(\mu /{\sigma }_{\mu })+4.05);$
    • (b)  
      ${({\mathrm{log}}_{10}{(\mu /{\sigma }_{\mu })-0.301)}^{2}/{0.39794}^{2}+(\varpi /{\sigma }_{\varpi })}^{2}/{4.5}^{2}\leqslant 1;$
  • 6.  
    The following conditions are all NOT met:

    • (a)  
      qflag bit 0 or 6 is set;
    • (b)  
      qflag bit 1, 2, or 5 is set AND UVW2 _signif < 10;
  • 7.  
    M_G > 4.09 OR M_G > 4.5457(G_BP − G_RP) + 4.0457;
  • 8.  
    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)].
• Data 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).
• Target priority options: 1400.
• Cadence options: bright_1x1, dark_1x2, dark_1x3.

• Description of selection criteria: Gaia and GALEX crossmatch, 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 (GMS) locus is defined by GMS = 0.00206868742x⁶ + 0.0401594518x⁵ − 0.842512410x⁴ + 4.89384979x³ − 12.3826637x² + 17.0197205x − 3.19987835, where x = G − G_RP. M_G is the Gaia absolute magnitude calculated with r_est.

  • 1.  
    r_lo ≤ 1500;
  • 2.  
    g_vis_per >5;
  • 3.  
    Neither of the following two conditions are met:

    • (a)  
      $({\mathrm{log}}_{10}(\mu /{\sigma }_{\mu })\lt 0.301)$ AND $(\varpi /{\sigma }_{\varpi }\gt -1.4996{\mathrm{log}}_{10}(\mu /{\sigma }_{\mu })-4.05)$ AND $(\varpi /{\sigma }_{\varpi }\lt 1.4995{\mathrm{log}}_{10}(\mu /{\sigma }_{\mu })+4.05);$
    • (b)  
      ${({\mathrm{log}}_{10}{(\mu /{\sigma }_{\mu })-0.301)}^{2}/{0.39794}^{2}+(\varpi /{\sigma }_{\varpi })}^{2}/{4.5}^{2}\leqslant 1;$
  • 4.  
    NUV > − 100;
  • 5.  
    FUV > − 100;
  • 6.  
    σ_NUV < 0.2;
  • 7.  
    σ_FUV < 0.2;
  • 8.  
    M_G > 4.0866;
  • 9.  
    H < 15;
  • 10.  
    ∣GMS − M_G ∣ ≤ 0.5;
  • 11.  
    r_est < 0.51 × 10^0.2291G .
• Data 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).
• Target priority options: 1400.
• Cadence options: bright_1x1, dark_1x2, dark_1x3.

• Description of selection criteria: the dust carton selects bright, nearby, midplane giants with the same quality cuts as 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 pc³ 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.

  • 1.  
    σ_ϖ /ϖ < 0.2;
  • 2.  
    1/ϖ < 5 kpc;
  • 3.  
    ∣z∣ < 0.2 kpc (using ϖ-based distances);
  • 4.  
    M_K < 2.6, adopting A_K = 0.918(H − 4.5);
  • 5.  
    (J − K)₀ > 0.5, where E(J − K) = 1.5A_K ;
  • 6.  
    H < 11.2;
  • 7.  
    gal_contam==0;
  • 8.  
    cc_flg==0;
  • 9.  
    0 < rd_flag < = 3;
  • 10.  
    ph_qual flag is A or B.
• Data sources: Gaia DR2 (ϖ, σ_ϖ ), 2MASS PSC (J, H, K, gal_contam, cc_flag, rd_flag, ph_qual).
• Target priority options: 2720.
• Cadence options: bright_1x1.

• Description 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.

  • 1.  
    G > 16;
  • 2.  
    L > 8 in at least one of the three eROSITA energy bands;
  • 3.  
    Detections in three eROSITA energy bands;
  • 4.  
    $\mathrm{log}\left({f}_{x}/{f}_{\mathrm{opt}}\right)\lt 2.7;$
  • 5.  
    radec_err > 0 and s/radec_err < 2.1, where s is the separation between the Gaia and eROSITA sources;
  • 6.  
    Neither of the following two conditions are met:

    • (a)  
      $({\mathrm{log}}_{10}(\mu /{\sigma }_{\mu })\lt 0.301)$ AND $(\varpi /{\sigma }_{\varpi }\gt -1.4996{\mathrm{log}}_{10}(\mu /{\sigma }_{\mu })-4.05)$ AND $(\varpi /{\sigma }_{\varpi }\lt 1.4995{\mathrm{log}}_{10}(\mu /{\sigma }_{\mu })+4.05);$
    • (b)  
      ${({\mathrm{log}}_{10}{(\mu /{\sigma }_{\mu })-0.301)}^{2}/{0.39794}^{2}+(\varpi /{\sigma }_{\varpi })}^{2}/{4.5}^{2}\leqslant 1;$
  • 7.  
    Is the optical source that meets the above criteria with the smallest separation s.
• Data sources: eROSITA (f_x , L, radec_err), Gaia DR2 (G, μ, σ_m u, ϖ, σ_ϖ , f_opt (from G)).
• Target priority options: 1910, 2400.
• Cadence options: bright_1x1, dark_1x2, dark_1x3.

• Description of selection criteria: optical counterpart to a candidate compact binary detected by eROSITA, chosen as the possible counterpart with the largest variability in Gaia DR2.

  • 1.  
    G > 16;
  • 2.  
    L > 8 in at least one of the three eROSITA energy bands;
  • 3.  
    Detections in three eROSITA energy bands;
  • 4.  
    $\mathrm{log}\left({f}_{x}/{f}_{\mathrm{opt}}\right)\lt 2.7;$
  • 5.  
    radec_err > 0 and s/radec_err < 2.1, where s is the separation between the Gaia and eROSITA sources;
  • 6.  
    Neither of the following two conditions are met:

    • (a)  
      $({\mathrm{log}}_{10}(\mu /{\sigma }_{\mu })\lt 0.301)$ AND $(\varpi /{\sigma }_{\varpi }\gt -1.4996{\mathrm{log}}_{10}(\mu /{\sigma }_{\mu })-4.05)$ AND $(\varpi /{\sigma }_{\varpi }\lt 1.4995{\mathrm{log}}_{10}(\mu /{\sigma }_{\mu })+4.05);$
    • (b)  
      ${({\mathrm{log}}_{10}{(\mu /{\sigma }_{\mu })-0.301)}^{2}/{0.39794}^{2}+(\varpi /{\sigma }_{\varpi })}^{2}/{4.5}^{2}\leqslant 1;$
  • 7.  
    Is the optical source that meets the above criteria with the largest variability ${\mathrm{log}}_{10}\left({\left(\tfrac{\mathrm{phot}\_{\rm{g}}\_{\rm{n}}\_\mathrm{obs}}{\mathrm{phot}\_{\rm{g}}\_\mathrm{mean}\_\mathrm{flux}\_\mathrm{over}\_\mathrm{error}}\right)}^{1/2}\right).$
• Data 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).
• Target priority options: 1900, 2400.
• Cadence options: bright_1x1, dark_1x2, dark_1x3.

• Description of selection criteria: optical or IR counterpart to a candidate stellar source detected by eROSITA. Counterpart identified using the techniques and data described in Freund et al. (2022).
• Data sources: eROSITA, Gaia DR2, 2MASS PSC.
• Target priority options: 1920, 2400.
• Cadence options: bright_1x1, dark_1x2, dark_1x3.

• Description of selection criteria: a simple color–magnitude cut effectively targets luminous cool giant stars ($\mathrm{median}(\mathrm{log}g)\sim 1.0\mbox{--}1.5$) with little (<6%) contamination from dwarf stars.

  • 1.  
    H < 11;
  • 2.  
    G − H > 3.5 or Gaia nondetection;
  • 3.  
    gal_contam==0;
  • 4.  
    cc_flg==0;
  • 5.  
    0 < rd_flag < = 3;
  • 6.  
    ph_qual flag is A or B.
• Data sources: Gaia DR2 (G), 2MASS PSC (H, gal_contam, cc_flg, rd_flag, ph_qual).
• Target priority options: 2710.
• Cadence options: bright_1x1.

• Description 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.

  • 1.  
    3 < G < 18;
  • 2.  
    G_BP > 13;
  • 3.  
    G_RP > 13.
• Data sources: Gaia DR2 (G, G_BP, G_RP), APOGEE DR16.
• Target priority options: 6100.
• Cadence options: bright_1x1.

• Description of selection criteria: catalog of cepheids compiled by Inno et al. (2021).
• Data sources: Inno et al. (2021).
• Target priority options: 2910.
• Cadence options: bright_3x1.

• Description of selection criteria: this carton uses color and magnitude cuts to select hot, young stars.

  • 1.  
    ϖ < 10^{(10−K−0.61)/5)};
  • 2.  
    G < 16;
  • 3.  
    J − K − 0.25(G − K) < 0.10;
  • 4.  
    J − K − 0.25(G − K) > − 0.30;
  • 5.  
    J − H < 0.15(G − K) + 0.05;
  • 6.  
    J − H > 0.15(G − K) − 0.15;
  • 7.  
    J − K < 0.23(G − K) + 0.03;
  • 8.  
    G > 2(G − K) + 3.0;
  • 9.  
    Crossmatch separation 1'';
  • 10.  
    RUWE < 1.4.
• Data sources: Gaia DR2 (G, ϖ, RUWE), 2MASS PSC (J, H, K).
• Target priority options: 2910.
• Cadence options: bright_3x1.

• Description of selection criteria: this carton selects stars previously observed at least three times with the APOGEE instrument if it was targeted as part of the main APOGEE sample or the APOGEE-2 binary program.

  • 1.  
    Presence in sdss_apogeeallstarmerge_r13 file (previously observed with APOGEE-1 and/or APOGEE-2);
  • 2.  
    APOGEE number of visits ≥3;
  • 3.  
    H < 11.5;
  • 4.  
    APOGEE TARGFLAGS includes one of the following: APOGEE_SHORT, APOGEE_INTERMEDIATE, APOGEE_LONG, APOGEE2_BIN;
  • 5.  
    Gaia-based distance.
• Data sources: APOGEE, 2MASS PSC (H), Gaia DR 2.
• Target priority options: 2510, 2520, 2530, 2540.
• Cadence options:bright_6x1 bright_6x2, bright_9x1, bright_9x2, bright_12x1, bright_12x2, bright_15x1, bright_15x2.

• 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.

  • 1.  
    H < 10.8;
  • 2.  
    J − K_s − (1.5 · 0.918(H − W2 − 0.05)) > = 0.05;
  • 3.  
    J_msigcom, H_msigcom, K_s _msigcom ≤ 0.1;
  • 4.  
    W2_sigmpro ≤ 0.1;
  • 5.  
    2MASS ph_qual any of the following: AAA, AAB, ABA, BAA, ABB, BAB, BBA, BBB;
  • 6.  
    2MASS gal_contam=0;
  • 7.  
    2MASS cc_flg=0;
  • 8.  
    2MASS rd_flg any of the following: 111, 112, 121, 211, 122, 212, 221, 222;
  • 9.  
    2MASS prox ≥ 6;
  • 10.  
    Gaia DR2 parallax exists;
  • 11.  
    Does not match a source in the 2MASS extended catalog.
• Data 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).
• Target priority options: 2515, 2525, 2535, 2545.
• Cadence options: bright_18x1.

• Description of selection criteria: IR bright targets in the 100 pc volume-limited region.

  • 1.  
    ϖ − σ_ϖ > 10;
  • 2.  
    H < 11;
  • 3.  
    astrometric_excess_noise <2 if in one of the following regions:

    • (a)  
      l ≤ 180 AND b < − 0.139l + 25 AND b > 0.139l − 25;
    • (b)  
      l > 180 AND b > − 0.139l + 25 AND b < 0.139l − 25;
    • (c)  
      $\sqrt{{(l-303.2)}^{2}+2* {(b+44.4)}^{2}}\lt 5;$
    • (d)  
      $\sqrt{{(l-280.3)}^{2}+2* {(b+33.0)}^{2}}\lt 8.$
• Data sources: Gaia DR2 (ϖ, σ_ϖ , astrometric_excess_noise, l, b), 2MASS PSC (H).
• Target priority options: 1805.
• Cadence options: bright_1x1.

• Description of selection criteria: optically bright targets in the 100 pc volume-limited region.

  • 1.  
    ϖ − σ_ϖ > 10;
  • 2.  
    astrometric_excess_noise <2 if in one of the following regions:

    • (a)  
      l ≤ 180 AND b < − 0.139l + 25 AND b > 0.139l − 25;
    • (b)  
      l > 180 AND b > − 0.139l + 25 AND b < 0.139l − 25;
    • (c)  
      $\sqrt{{(l-303.2)}^{2}+2* {(b+44.4)}^{2}}\lt 5;$
    • (d)  
      $\sqrt{{(l-280.3)}^{2}+2* {(b+33.0)}^{2}}\lt 8.$
• Data sources: Gaia DR2 (ϖ, σ_ϖ , astrometric_excess_noise, l, b, G).
• Target priority options: 1800.
• Cadence options: bright_2x1, dark_2x1.

• Description of selection criteria: IR bright targets in the 250 pc volume-limited region.

  • 1.  
    $G+5{\mathrm{log}}_{10}(\varpi /1000)+5\lt 6;$
  • 2.  
    ϖ − σ_ϖ > 4;
  • 3.  
    H < 11;
  • 4.  
    astrometric_excess_noise <2 if in one of the following regions:

    • (a)  
      l ≤ 180 AND b < − 0.139l + 25 AND b > 0.139l − 25;
    • (b)  
      l > 180 AND b > − 0.139l + 25 AND b < 0.139l − 25;
    • (c)  
      $\sqrt{{(l-303.2)}^{2}+2* {(b+44.4)}^{2}}\lt 5;$
    • (d)  
      $\sqrt{{(l-280.3)}^{2}+2* {(b+33.0)}^{2}}\lt 8.$
• Data sources: Gaia DR2 (ϖ, σ_ϖ , astrometric_excess_noise, l, b, G), 2MASS PSC (H).
• Target priority options: 1815.
• Cadence options: bright_1x1.

• Description of selection criteria: optically bright targets in the 250 pc volume-limited region.

  • 1.  
    $G+5{\mathrm{log}}_{10}(\varpi /1000)+5\lt 6;$
  • 2.  
    ϖ − σ_ϖ > 4;
  • 3.  
    astrometric_excess_noise <2 if in one of the following regions:

    • (a)  
      l ≤ 180 AND b < − 0.139l + 25 AND b > 0.139l − 25;
    • (b)  
      l > 180 AND b > − 0.139l + 25 AND b < 0.139l − 25;
    • (c)  
      $\sqrt{{(l-303.2)}^{2}+2* {(b+44.4)}^{2}}\lt 5;$
    • (d)  
      $\sqrt{{(l-280.3)}^{2}+2* {(b+33.0)}^{2}}\lt 8.$
• Data sources: Gaia DR2 (ϖ, σ_ϖ , astrometric_excess_noise, l, b, G), 2MASS PSC (H).
• Target priority options: 1810.
• Cadence options: bright_2x1, dark_2x1.

• Description of selection criteria: stars with TESS 2 minute cadence data taken during the nominal 2 year mission, prioritizing those that are either TOIs or community TOIs.

  • 1.  
    7 < H < 12.
• Data sources: 2MASS PSC (H), TESS.
• Target priority options: 2600, 2605, 2610.
• Cadence options: bright_1x1, bright_1x2, bright_1x3, bright_1x4, bright_1x5, bright_1x6.

• Description 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 lightcurve data.

  • 1.  
    J − K > 0.5;
  • 2.  
    H < 12;
  • 3.  
    T < 13;
  • 4.  
    $H-10+5{\mathrm{log}}_{10}\varpi \lt 1;$
  • 5.  
    ∣b∣ > 20.
• Data sources: Gaia DR2 (ϖ), 2MASS PSC (J, H, K), TESS (T).
• Target priority options: 2800.
• Cadence options: bright_1x1, bright_1x2, bright_1x3, bright_1x4, bright_1x5, bright_1x6.

• Description of selection criteria: all sufficiently bright WD candidates, where P_WD is the probability a target is a WD.

  • 1.  
    G < 20;
  • 2.  
    P_WD > 0.5.
• Data sources: Gaia DR2 (G), Gentile Fusillo et al. (2019, P_WD).
• Target priority options: 1400.
• Cadence options: dark_2x1.

• Description of selection criteria: IR bright YSO candidates associated with young moving groups, as identified by Kounkel et al. (2020).

  • 1.  
    H < 13;
  • 2.  
    age <10^7.5 yr.
• Data sources: 2MASS PSC (H), Kounkel et al. (2020, age).
• Target priority options: 2705.
• Cadence options: bright_3x1.

• Description of selection criteria: optically bright YSO candidates associated with young moving groups, as identified by Kounkel et al. (2020).

  • 1.  
    G_RP < 15.5;
  • 2.  
    age <10^7.5 yr.
• Data sources: Gaia DR2 (G_RP), Kounkel et al. (2020, age).
• Target priority options: 2705.
• Cadence options: bright_3x1, bright_4x1, bright_5x1, bright_6x1.

• Description of selection criteria: YSOs in the central molecular zone, the most extreme star-forming environment in the Milky Way.

  • 1.  
    H < 13;
  • 2.  
    [8.0] − [24] > 2.5, in the Gutermuth & Heyer (2015) catalog;
  • 3.  
    ϖ < 0.2 or not measured.
• Data sources: Gaia DR2 (ϖ), 2MASS PSC (H), Spitzer ([8.0], [24]).
• Target priority options: 2700.
• Cadence options: bright_3x1.

• Description of selection criteria: YSOs expected to have protoplanetary disks, as identified by larger IR excesses.

  • 1.  
    H < 13;
  • 2.  
    W1 − W2 > 0.25;
  • 3.  
    W2 − W3 > 0.50;
  • 4.  
    W3 − W4 > 1.50;
  • 5.  
    ϖ > 0.3 mas.
• Data sources: Gaia DR2 (ϖ), 2MASS PSC (H), AllWise (W1, W2, W3, W4).
• Target priority options: 2705.
• Cadence options: bright_3x1.

• Description of selection criteria: optically bright YSOs expected to have protoplanetary disks, as identified by larger IR excesses.

  • 1.  
    G_RP < 8.5;
  • 2.  
    W1 − W2 > 0.25;
  • 3.  
    W2 − W3 > 0.50;
  • 4.  
    W3 − W4 > 1.50;
  • 5.  
    ϖ > 0.3 mas.
• Data sources: Gaia DR2 (G_RP, ϖ), AllWise (W1, W2, W3, W4).
• Target priority options: 2705.
• Cadence options: bright_3x1, bright_4x1, bright_5x1, bright_6x1.

• Description of selection criteria: deeply embedded YSO candidates too optically faint for parallax measurements have more stringent IR color cuts to avoid contamination with reddened field stars.

  • 1.  
    H < 13;
  • 2.  
    G > 18.5 or undetected;
  • 3.  
    J − H > 1;
  • 4.  
    H − K > 0.5;
  • 5.  
    W1–W2 > 0.5;
  • 6.  
    W2–W3 > 1;
  • 7.  
    W3–W4 > 1.5;
  • 8.  
    W3–W4 > 0.8(W1 − W2) + 1.1.
• Data sources: Gaia DR2 (G), 2MASS PSC (J, H, K), AllWise (W1, W2, W3, W4).
• Target priority options: 2705.
• Cadence options: bright_3x1.

• Description of selection criteria: YSOs with strong nebular emission should saturate in the long AllWise bands and are identified with short-wavelength color cuts.

  • 1.  
    H < 13;
  • 2.  
    (no W4 AND W2 − W3 > 4) OR (no W3, W4 AND J − H > 1.1);
  • 3.  
    b < 5°;
  • 4.  
    b > − 5° OR l > 180°.
• Data sources: 2MASS PSC (J, H), AllWise (W1, W2, W3, W4).
• Target priority options: 2705.
• Cadence options: bright_3x1.

• Description of selection criteria: IR bright YSO candidates based on their location above the main sequence, as identified by Zari et al. (2018) or McBride et al. (2021).

  • 1.  
    H < 13.
• Data sources: 2MASS PSC (H).
• Target priority options: 2700.
• Cadence options: bright_3x1.

• Description 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).

  • 1.  
    G_RP < 15.5.
• Data sources: Gaia DR2 (G_RP).
• Target priority options: 2700.
• Cadence options: bright_3x1, bright_4x1, bright_5x1, bright_6x1.

• Description 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 ${V}_{X}=\sqrt{{N}_{\mathrm{obs}}{\sigma }_{\overline{{I}_{X}}}/(\overline{{I}_{X}})}$, where $\overline{{I}_{X}}$ is the mean flux and ${\sigma }_{\overline{{I}_{X}}}$ its associated error. Below, ${M}_{X}={G}_{X}-5({\mathrm{log}}_{10}(1000/\varpi )-1)$.

  • 1.  
    H < 13;
  • 2.  
    G < 18.5;
  • 3.  
    ϖ > 0.3;
  • 4.  
    V_G > 0.02;
  • 5.  
    V_BP > 0.02;
  • 6.  
    V_RP > 0.02;
  • 7.  
    ${V}_{G}^{0.75}\lt {V}_{\mathrm{BP}}\lt {V}_{G};$
  • 8.  
    $0.75{V}_{G}\lt {V}_{\mathrm{RP}}\lt {V}_{G}^{0.95};$
  • 9.  
    G_BP − G_RP > 1.3.
  • 10.  
    ${M}_{\mathrm{BP}}\gt 5{\mathrm{log}}_{10}{V}_{\mathrm{BP}}+11;$
  • 11.  
    2.5(G_BP − G_RP) − 1 < M_G < 2.5*(G_BP − G_RP) + 2.5.
• Data sources: Gaia DR2 (G, G_RP, G_BP, ϖ, $\overline{{I}_{X}}$ , ${\sigma }_{\overline{{I}_{X}}}$ ), 2MASS PSC (H).
• Target priority options: 2705.
• Cadence options: bright_3x1.

• Description of selection criteria: YSO candidates that are variable in the Gaia bands, to be observed with BOSS. Variability in a given band X is defined by ${V}_{X}=\sqrt{{N}_{\mathrm{obs}}{\sigma }_{\overline{{I}_{X}}}/(\overline{{I}_{X}})}$, where $\overline{{I}_{X}}$ is the mean flux and ${\sigma }_{\overline{{I}_{X}}}$ its associated error. Below, ${M}_{X}={G}_{X}-5({\mathrm{log}}_{10}(1000/\varpi )-1)$.

  • 1.  
    H < 13;
  • 2.  
    G < 18.5;
  • 3.  
    ϖ > 0.3;
  • 4.  
    V_G > 0.02;
  • 5.  
    V_BP > 0.02;
  • 6.  
    V_RP > 0.02;
  • 7.  
    ${V}_{G}^{0.75}\lt {V}_{\mathrm{BP}}\lt {V}_{G};$
  • 8.  
    $0.75{V}_{G}\lt {V}_{\mathrm{RP}}\lt {V}_{G}^{0.95};$
  • 9.  
    G_BP − G_RP > 1.3;
  • 10.  
    ${M}_{\mathrm{BP}}\gt 5{\mathrm{log}}_{10}{V}_{\mathrm{BP}}+11;$
  • 11.  
    2.5(G_BP − G_RP) − 1 < M_G < 2.5*(G_BP − G_RP) + 2.5.
• Data sources: Gaia DR2 (G, G_RP, G_BP, ϖ, $\overline{{I}_{X}}$ , ${\sigma }_{\overline{{I}_{X}}}$ ), 2MASS PSC (H).
• Target priority options: 2705.
• Cadence options: bright_3x1, bright_4x1, bright_5x1, bright_6x1.

• target_selection plan: 0.5.0.
• target_selection tag: 0.3.0.
• Summary: 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 preselected 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.
• Simplified description of selection criteria: select all objects from the SDSS DR16 QSO catalog that have SDSS 16.0 < i_psf < 19.1 AB and that lie within 149 of at least one AQMES-medium field location.
• Target priority options: 1100.
• Cadence options: dark_10x4_4yr.
• Implementation: bhm_aqmes.py.
• Number of targets: 2663.

• target_selection plan: 0.5.0.
• target_selection tag: 0.3.0.
• Summary: 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 preselected 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.
• Simplified description of selection criteria: select all objects from the SDSS DR16 QSO catalog that have SDSS 19.1 < i_psf < 21.0 AB and that lie within 149 of at least one AQMES-medium field location.
• Target priority options: 3100.
• Cadence options: dark_10x4_4yr.
• Implementation: bhm_aqmes.py.
• Number of targets: 16,853.

• target_selection plan: 0.5.4.
• target_selection tag: 0.3.5.
• Summary: 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 fields that overlapped with the SPIDERS footprint (approximately 180º < l < 360°) 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.
• Simplified description of selection criteria: select all objects from the SDSS DR16 QSO catalog that have SDSS 16.0 < i_psf < 19.1 AB and that lie within 149 of at least one AQMES wide-field location.
• Target priority options: 1210, 1211.
• Cadence options: dark_2x4.
• Implementation: bhm_aqmes.py.
• Number of targets: 24,142.

• target_selection plan: 0.5.4.
• target_selection tag: 0.3.5.
• Summary: 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 fields that overlapped with the SPIDERS footprint (approximately 180º < l < 360º) 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.
• Simplified description of selection criteria: select all objects from the SDSS DR16 QSO catalog that have SDSS 19.1 < i_psf < 21.0 AB and that lie within 149 of at least one AQMES wide-field location.
• Target priority options: 3210, 3211.
• Cadence options: dark_2x4.
• Implementation: bhm_aqmes.py.
• Number of targets: 99,586.

• target_selection plan: 0.5.4.
• target_selection tag: 0.3.5.
• Summary: spectroscopically confirmed optically bright SDSS QSOs, selected from the SDSS QSO catalog (DR16Q; Lyke et al. 2020). Located anywhere within the SDSS DR16Q footprint.
• Simplified description of selection criteria: select all objects from the SDSS DR16 QSO catalog that have SDSS 16.0 < i_psf < 19.1 AB.
• Target priority options: 3300, 3301.
• Cadence options: dark_1x4.
• Implementation: bhm_aqmes.py.
• Number of targets: 83,163.

• target_selection plan: 0.5.4.
• target_selection tag: 0.3.5.
• Summary: spectroscopically confirmed optically faint SDSS QSOs, selected from the SDSS QSO catalog (DR16Q; Lyke et al. 2020). Located anywhere within the SDSS DR16Q footprint.
• Simplified description of selection criteria: select all objects from the SDSS DR16 QSO catalog that have SDSS 19.1 < i_psf < 21.0 AB.
• Target priority options: 3302, 3303.
• Cadence options: dark_1x4.
• Implementation: bhm_aqmes.py.
• Number of targets: 424,163.

• target_selection plan: 0.5.4.
• target_selection tag: 0.3.5.
• Summary: 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.
• Simplified description of selection criteria: select all objects from the SDSS DR16 QSO catalog that have SDSS 14.0 < i_psf < 18.0 AB.
• Target priority options: 4040, 4041.
• Cadence options: bright_3x1.
• Implementation: bhm_aqmes.py.
• Number of targets: 10,848.

• target_selection plan: 0.5.0.
• target_selection tag: 0.3.0.
• Summary: 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 (plus one backup) well-known survey fields (SDSS-RM, COSMOS, XMM-LSS, ECDFS, CVZ-S/SEP, and ELIAS-S1).
• Simplified description of selection criteria: starting from a parent catalog of optically selected objects in the RM fields (as presented by Yang & Shen 2023), 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 2023); (iii) do not have significant detections (>3σ) 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.
• Target priority options: 900–1050.
• Cadence options: dark_174x8, dark_100x8.
• Implementation: bhm_rm.py.
• Number of targets: 943.

• target_selection plan: 0.5.0.
• target_selection tag: 0.3.0.
• Summary: a sample of candidate QSOs selected via the methods presented by Yang & Shen (2023). These targets are located within five (plus one backup) well-known survey fields (SDSS-RM, COSMOS, XMM-LSS, ECDFS, CVZ-S/SEP, and ELIAS-S1).
• Simplified description of selection criteria: starting from a parent catalog of optically selected objects in the RM fields (as presented by Yang & Shen 2023), 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 2023); (iii) do not have significant detections (>3σ) 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.
• Target priority options: 900–1050.
• Cadence options: dark_174x8, dark_100x8.
• Implementation: bhm_rm.py.
• Number of targets: 3721.

• target_selection plan: 0.5.0.
• target_selection tag: 0.3.0.
• Summary: a sample of candidate QSOs selected via their optical variability properties, as presented by Yang & Shen (2023). These targets are located within five (plus one backup) well-known survey fields (SDSS-RM, COSMOS, XMM-LSS, ECDFS, CVZ-S/SEP, and ELIAS-S1).
• Simplified description of selection criteria: starting from a parent catalog of optically selected objects in the RM fields (as presented by Yang & Shen 2023), select candidate QSOs that satisfy all of the following: (i) have significant variability in the Dark Energy Survey or Pan-STARRS1 multi-epoch photometry ($\mathrm{var}\_\mathrm{sn}[g]\gt 3$ 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 2023); (iii) do not have significant detections (>3σ) 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.
• Target priority options: 900–1050.
• Cadence options: dark_174x8, dark_100x8.
• Implementation: bhm_rm.py.
• Number of targets: 934.

• target_selection plan: 0.5.0.
• target_selection tag: 0.3.0.
• Summary: a sample of known QSOs identified through optical spectroscopy from various projects, as collated by Yang & Shen (2023). These targets are located within five (plus one backup) well-known survey fields (SDSS-RM, COSMOS, XMM-LSS, ECDFS, CVZ-S/SEP, and ELIAS-S1).
• Simplified description of selection criteria: starting from a parent catalog of optically selected objects in the RM fields (as presented by Yang & Shen 2023), select targets that 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, and 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 2023); (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.
• Target priority options: 900–1050.
• Cadence options: dark_174x8, dark_100x8.
• Implementation: bhm_rm.py.
• Number of targets: 3022.

• target_selection plan: 0.5.15.
• target_selection tag: 0.3.14.
• Summary: X-ray sources from the CSC2.0 source catalog with near-IR counterparts in 2MASS PSC
• 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) near-IR counterpart is from the 2MASS catalog; and (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.
• Target priority options: 2930–2939.
• Cadence options: bright_1x1,bright_3x1.
• Implementation: bhm_csc.py.
• Number of targets: 48,928.

• target_selection plan: 0.5.15.
• target_selection tag: 0.3.14.
• Summary: X-ray sources from the CSC2.0 source catalog with counterparts in Pan-STARRS1 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 Pan-STARRS1 or Gaia DR2 catalogs; and (ii) optical flux/magnitude is in the accepted range for SDSS-V: Pan-STARRS1 g_psf, r_psf, i_psf, z_psf > 13.5 AB and non-Null i_psf (objects with Pan-STARRS1 counterparts); G, G_RP > 13.0 Vega (Gaia DR2 counterparts). Deprioritize targets that already have good-quality SDSS spectroscopy. Allocate cadence (exposure time) requests based on optical brightness (Pan-STARRS1 i_psf or Gaia G).
• Target priority options: 1920–1939, 2920–2939.
• Cadence options: bright_1x1,dark_1x2,dark_1x4.
• Implementation: bhm_csc.py.
• Number of targets: 122,731.

• target_selection plan: 0.5.0.
• target_selection tag: 0.3.0.
• Summary: a sample of optically bright candidate AGNs 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.
• Simplified 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.
• Target priority options: 4040.
• Cadence options: bright_2x1.
• Implementation: bhm_gua.py.
• Number of targets: 254,601.

• target_selection plan: 0.5.0.
• target_selection tag: 0.3.0.
• Summary: a sample of optically faint candidate AGNs 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.
• Simplified 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 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.
• Target priority options: 3400.
• Cadence options: dark_1x4.
• Implementation: bhm_gua.py.
• Number of targets: 2,156,582.

• target_selection plan: 0.5.16.
• target_selection tag: 0.3.13.
• Summary: 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.
• Simplified 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; and (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).
• Target priority options: 7100.
• Cadence options: bright_1x1, dark_1x1, dark_1x4.
• Implementation: bhm_galaxies.py.
• Number of targets: 7,320,203.