The 16th Data Release of the Sloan Digital Sky Surveys: First Release from the APOGEE-2 Southern Survey and Full Release of eBOSS Spectra

The main path to access the raw and reduced imaging and spectroscopic data directly, as well as obtain intermediate data products and VACs, is through the SDSS Science Archive Server (SAS, https://data.sdss.org/sas/). Note that all previous data releases are also available on this server, but we recommend that users always adopt the latest data release, as these are reduced with the latest versions of the data reduction software. The SAS is a file-based system, which allows data downloads by browsing or through tools such as rsync, wget and Globus Online (see https://www.sdss.org/dr16/data_access/bulk for more details). The content of each data product on the SAS is outlined in its data model, which can be accessed through https://data.sdss.org/datamodel/.

Most of the reduced images and spectra on the SAS are also accessible through the Science Archive Webapp (SAW), which provides the user with options to display spectra and overlay model fits. The SAW includes search options to access specific subsamples of spectra, e.g., based on coordinates, redshift, and/or observing programs. Searches can also be saved as "permalinks" to allow sharing with collaborators and future use. Links are provided to download the spectra directly from the SAS, and to open SkyServer Explore pages for the objects displayed (see below for a description of the SkyServer). The SAW contains imaging, optical single-fiber spectra (SDSS-I/II, SEGUE, BOSS, eBOSS), infrared spectra (APOGEE-1/2), and stellar spectra of the MaStar stellar library. All of these webapps are linked from https://dr16.sdss.org/. Just like the SAS, the SAW provides access to previous data releases (back to DR8).

Integral-field spectroscopic data (MaNGA) are not available in the SAW because they follow a different data format from the single-object spectra. Instead, the MaNGA data can be accessed through Marvin (https://dr16.sdss.org/marvin/; Cherinka et al. 2019). Marvin can be used to both visualize and analyze MaNGA data products and perform queries on MaNGA metadata remotely. Marvin also contains a suite of Python tools, available through pip-install, that simplify interacting with the MaNGA data products and metadata. More information, including installation instructions for Marvin, can be found here: https://sdss-marvin.readthedocs.io/en/stable/. In DR16, although no new MaNGA data products are included, Marvin has been upgraded by providing access to a number of MaNGA VACs based on DR15 data.

The SDSS catalogs can be found and queried on the Catalog Archive Server (CAS; Thakar et al. 2008). These catalogs contain photometric and spectroscopic properties, as well as derived data products. Several value-added catalogs are also available on the CAS. For quick inspection of objects or small queries, the SkyServer webapp (https://skyserver.sdss.org) is the recommended route to access the catalogs: it contains among other facilities the Quick Look and Explore tools, as well as the option for SQL queries in synchronous mode directly in the browser. The SkyServer also contains tutorials and examples of SQL syntax (http://skyserver.sdss.org/public/en/help/docs/docshome.aspx). For larger queries, CASJobs (https://skyserver.sdss.org/casjobs) should be used, as it allows for asynchronous queries in batch mode. Users of CASJobs will need to create a (cost-free) personal account, which comes with storage space for query results (Li & Thakar 2008). A third way to access the SDSS catalogs is through the SciServer (https://www.sciserver.org), which is integrated with the CAS. SciServer allows users to run Jupyter notebooks in Docker containers, among other services.

We are providing access to a growing set of Jupyter notebooks that have been developed for introductory¹⁴¹ and upper-level¹⁴² university astronomy laboratory courses. These Python-based activities are designed to be run on the SciServer platform,¹⁴³ which enables the analysis and visualization of the vast SDSS data set from a web browser, without requiring any additional software or data downloads.

Additionally, Voyages (http://voyages.sdss.org/) provides activities and resources to help younger audiences explore the SDSS data. Voyages has been specifically developed to be used in secondary schools, and contains pointers to K-12 US science standards. A Spanish language version of these resources is now available at http://voyages.sdss.org/es.

The APOGEE-2S Survey has been enabled by the construction of a second APOGEE spectrograph. The second instrument is a near duplicate of the first with comparable performance, simultaneously delivering 300 spectra in the H-band wavelength regime (λ = 1.5–1.7 μm) at a resolution of R ∼ 22,500. Slight differences occur between the two instruments with respect to image quality and resolution across the detectors as described in detail in Wilson et al. (2019).

The telescopes of the Northern and Southern Hemisphere sites have the same apertures. However, because the du Pont telescope was designed with a slower focal ratio (f/7.5) than the Sloan Foundation telescope (f/5), the resulting field of view for APOGEE-2S is smaller than that for APOGEE-2N and the fibers subtend a smaller angular area. The difference in field of view is evident in Figure 1 by comparing the size of the red points (LCO fields) to those shown in blue or cyan (APO fields). However, the image quality (seeing) at LCO is generally better than that at APO, and this roughly compensates for the smaller angular diameter fibers such that the typical throughput at LCO is similar to, or even better than, that obtained at APO.

Extensive descriptions of the target selection and strategy are found in Zasowski et al. (2013) for APOGEE-1 and in Zasowski et al. (2017) for APOGEE-2. Details about the final selection method used for APOGEE-2N and APOGEE-2S will be presented in R. Beaton, et al. (2020, in preparation) and F. Santana et al. (2020, in preparation), respectively. These papers will provide descriptions for the ancillary and external programs, modifications to original targeting strategies required by evaluation of their effectiveness, and modifications of the field plan as required by weather gains or losses. We include all targeting information using flags and also provide input catalogs on the SAS.

APOGEE-2 scientific goals are implemented in a three-tier strategy, where individual programs aimed at specific science goals are classified as core, goal, or ancillary. The core programs produce a systematic exploration of the major components of the bulge, disk, and halo and are given the highest priority for implementation. The goal programs have more focused science goals, for example follow-up of Kepler Objects of Interest, and are implemented as a secondary priority. Ancillary programs are implemented at the lowest priority; such programs were selected from a competitive proposal process and have only been implemented for APOGEE-2N. Generally, the APOGEE-2N and APOGEE-2S survey science are implemented in the same manner.

In addition to a target selection analogous to that for the northern observations, APOGEE-2S includes external programs selected by the Chilean National Time Allocation Committee or the Observatories of the Carnegie Institution for Science and led by individual scientists (or teams) who can be external to the SDSS-IV collaboration. External programs can be "contributed," or proprietary; contributed data are processed through the normal APOGEE DRPs and are released along with other APOGEE data whereas proprietary programs are not necessarily processed through the standard pipelines or released with the public DRs.¹⁴⁴ The selection of external program targets does not follow the standard APOGEE survey criteria in terms of signal-to-noise ratio (S/N) or even source catalogs; the scientists involved were able to exercise great autonomy in target selection (e.g., no implementation of color cuts). External programs are implemented as classical observing programs with observations only occurring for a given program on nights assigned to it.

The APOGEE portion of DR16 includes 437,485 unique stars. Among these, 308,000 correspond to core science targets, 112,000 to goal science targets, 13,000 to ancillary APOGEE-2N program targets, and 37,000 to APOGEE-2S external program targets. These numbers add up to more than 437,485 due to some stars being in multiple categories.

The basic procedure for processing and analysis of APOGEE data is similar to that of DR14 data (Abolfathi et al. 2018; Holtzman et al. 2018), but a few notable differences are highlighted here. Full details, including verification analyses, are presented in Jönsson et al. (2020).

4.3.1. Spectral Reduction and RV Determinations

4.3.2. Atmospheric Parameter and Element Abundance Derivations

The quality of the DR16 results for radial velocities, stellar parameters, and abundances is similar to that of previous APOGEE data releases. Figure 3 shows a ${T}_{\mathrm{eff}}$–$\mathrm{log}\,g$ diagram for the main sample APOGEE stars in DR16. The use of MARCS atmosphere models (Gustafsson et al. 2008) across the entire ${T}_{\mathrm{eff}}$–$\mathrm{log}\,g$ range has significantly improved results for cooler giants; previously, Kurucz atmosphere models (Castelli & Kurucz 2003) were used for the latter stars, and discontinuities were visible at the transition point between MARCS and Kurucz. While the stellar parameters are overall an improvement from previous DRs, we still apply external calibrations to both $\mathrm{log}\,g$ and ${T}_{\mathrm{eff}}$. These calibrations are discussed fully in Jönsson et al. (2020), who also describe the features in Figure 3 in more detail.

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Several fields were observed with both the APOGEE-N and APOGEE-S instruments. Comparing the results, we find close agreement in the derived stellar parameters and abundances, with mean offsets of Δ${T}_{\mathrm{eff}}$ ∼ 10 K, Δ$\mathrm{log}\,g$ ∼ 0.02 dex, and abundance offsets of <0.02 dex for most elements.

There are six APOGEE-associated VAC's in DR16. A brief description of each VAC and the corresponding publications are given below. They are also listed in Table 2.

4.5.1. APOGEE Red Clump Catalog

4.5.2. APOGEE-astroNN

4.5.3. APOGEE-Joker

4.5.4. Open Cluster Chemical Abundances and Mapping

4.5.5. APOGEE DR16 StarHorse Distances and Extinctions

The first generation of the SDSS produced a spectroscopic LRG sample (Eisenstein et al. 2001) that led to a detection of the BAO feature in the clustering of matter (Eisenstein et al. 2005) and the motivation for dedicated LSS surveys within the SDSS. Over the period 2009–2014, BOSS completed a BAO program using more than 1.5 million galaxy spectra spanning redshifts 0.15 < z < 0.75 and more than 150,000 quasars at z > 2.1 that illuminate the matter density field through the Lyα forest. Operating over the period 2014–2019, eBOSS is the third and final in the series of SDSS LSS surveys.

The eBOSS survey was designed to obtain spectra of four distinct target classes to trace the underlying matter density field over an interval in cosmic history that was largely unexplored during BOSS. The LRG sample covers the lowest-redshift interval within eBOSS, providing an expansion of the high-redshift tail of the BOSS galaxy sample (Reid et al. 2016) to a median redshift z = 0.72. Galaxy targets (Prakash et al. 2016) were selected from imaging catalogs derived from Wide-field Infrared Survey Explorer (WISE; Wright et al. 2010) and SDSS DR13 imaging data. A new sample of ELG targets covering 0.6 < z < 1.1 was observed over the period 2016–2018, leading to the highest-redshift galaxy sample from the SDSS. Galaxy targets were identified using imaging from the Dark Energy Camera (DECam; Flaugher et al. 2015). The ELG selection (Raichoor et al. 2017) reaches a median redshift z = 0.85 and represents the first application of the DECam Legacy Survey data (DECaLS; Dey et al. 2019) to spectroscopic target selection in any large clustering survey. The quasar sample covers the critical redshift range 0.8 < z < 2.2 and is derived from WISE infrared and SDSS optical imaging data (Myers et al. 2015). Finally, new spectra of z > 2.1 quasars were obtained to enhance the final BOSS Lyα forest measurements (Bautista et al. 2017; du Mas des Bourboux et al. 2017). A summary of all these target categories, with redshift ranges and numbers, is provided in Table 3.

The surface area and target densities of each sample were chosen to maximize sensitivity to the clustering of matter at the BAO scale. The first major clustering result from eBOSS originated from the two year DR14 quasar sample. Using 147,000 quasars, a measurement of the spherically averaged BAO distance at an effective redshift z = 1.52 was performed with 4.4% precision (Ata et al. 2018). The DR14 LRG sample was used successfully to measure the BAO distance scale at 2.6% precision (Bautista et al. 2018) while the DR14 high-redshift quasar sample led to improved measurements of BAO in the auto-correlation of the Lyα forest (de Sainte Agathe et al. 2019) and the cross-correlation of the Lyα forest with quasars (Blomqvist et al. 2019). The DR14 samples have also been used to perform measurements of redshift–space distortions (RSD) (e.g., Zarrouk et al. 2018), tests of inflation (e.g., Castorina et al. 2019), and new constraints on the amplitude of matter fluctuations and the scalar spectral index (e.g., Chabanier et al. 2019).

5.1.1. Scope of eBOSS

With the completion of eBOSS, the BOSS and eBOSS samples provide six distinct target samples covering the redshift range 0.2 < z < 3.5. The number of targets for each sample is summarized in Table 3 and the surface density of each sample is shown in Figure 4.

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Figure 5 shows the DR16 eBOSS spectroscopic coverage in equatorial coordinates. For comparison, the SDSS-III BOSS coverage is shown in gray. The programs that define the unique eBOSS clustering samples are SEQUELS (Sloan Extended Quasar, ELG, and LRG Survey; initiated during SDSS-III; LRG and quasars), eBOSS LRG+QSO (the primary program in SDSS-IV observing LRGs and quasars or quasi-stellar objects (QSOs)), and ELG (new to DR16).

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5.1.2. Changes to the eBOSS Spectral Reduction Algorithms

5.1.3. eBOSS VACs

5.1.4. Anticipated Cosmology Results from eBOSS

The SDSS-RM (Shen et al. 2015a) project is a dedicated multi-object RM program that began observations as a part of SDSS-III in 2014 January. Although not specifically established as a survey within eBOSS, observations of those same targets using the BOSS spectrograph continued through SDSS-IV. The SDSS-RM program monitors a sample of 849 quasars in a single ∼7 deg² pointing (observed with three plates, 7338, 7339, and 7340, with identical targets), with the overall goal of measuring black hole masses via RM in ∼100 quasars at a wide range of redshifts (details on the quasar sample itself are provided by Shen et al. 2019b). During the first season of SDSS-III monitoring, SDSS-RM obtained 32 epochs of SDSS spectroscopy, and has subsequently obtained ∼12 epochs yr⁻¹ during 2015–2017 and ∼6 epochs yr⁻¹ during 2018–2020 as part of SDSS-IV. The field has also been monitored photometrically with the Canada–France–Hawaii Telescope (CFHT) and the Steward Observatory Bok telescope in order to increase the observing cadence and the overall yield of RM time-lag measurements. The SDSS-RM field is also coincident with the Pan-STARRS 1 (PS1 Kaiser et al. 2010) Medium Deep Field MD07, and thus has been monitored photometrically since 2010. Observations with SDSS and the Bok telescope will continue through 2020.

The program has been largely successful in obtaining RM measurements: Shen et al. (2016b) reported several RM measurements from the program after analyzing the first year of spectroscopic data only, and Li et al. (2017) measured composite RM signals in the same data set. Grier et al. (2017) combined the first year of spectroscopy with the first year of photometry and recovered 44 lag measurements in the lowest-redshift subsample using the Hβ emission line. With the additional years of SDSS-IV monitoring included, Grier et al. (2019) reported 48 lag measurements using the Civ emission line; the addition of another year of SDSS spectroscopy and the inclusion of the PS1 photometric monitoring from 2010 to 2013 demonstrated the utility of longer time baselines in measuring additional lags (Shen et al. 2019a). Homayouni et al. (2019) measured inter-band continuum lags in many sources, allowing for investigations of accretion-disk properties. Additional studies based on SDSS-RM data that aim to evaluate and improve RM and black hole-mass measurement methodologies have also been completed (Li et al. 2019; Wang et al. 2019). The final SDSS-RM data set, which will make use of the PS1 monitoring of the SDSS-RM field and seven years of SDSS spectroscopic monitoring, will span more than 10 years and allow for the measurement of lags in the highest-luminosity subset of the quasar sample.

The SDSS-RM data set is extremely rich and allows for many other types of investigations beyond RM and black hole masses. The SDSS-RM group has also reported on many other topics, such as studies of quasar host galaxies (Matsuoka et al. 2015; Shen et al. 2015b; Yue et al. 2018), broad absorption-line (BAL) variability (Grier et al. 2015; Hemler et al. 2019), studies of extreme quasar variability (Dexter et al. 2019), and investigations of quasar emission-line properties (Sun et al. 2015, 2018; Denney et al. 2016a, 2016b; Shen et al. 2016a). RM observing will continue through 2020 at APO. Building on this program in SDSS-IV, an expanded multi-object spectroscopic RM program is included in the black hole mapper (BHM) program in the upcoming SDSS-V survey post-2020 (see Section 7).

In addition to the dedicated RM program, there were several fields in SDSS-III and SDSS-IV that were observed multiple times and thus offer similar potential for time-domain spectroscopic analyses. Those fields with at least four observations are as follows.

• 1.  
  Plates 3615 and 3647: contain the standard BOSS selection of targets. These two plates have identical science targets and contain 14 epochs that are classified as "good" observations during SDSS-III.
• 2.  
  Plate 6782: contains targets selected to be likely quasars based on variability from multi-epoch imaging data in Stripe 82 (York et al. 2000; Ivezić et al. 2007).¹⁵⁰ This plate contains four epochs that are classified as "good" observations during SDSS-III.
• 3.  
  Plates 7691 and 10000: contain a standard eBOSS selection of LRG, quasar, SPIDERS, and TDSS targets. The two plates have identical selections and were observed nine times during SDSS-IV.
• 4.  
  Plate 9414: contains ELG targets and TDSS targets from Stripe 82 and was observed four times to develop higher-S/N spectra that could be used to test the automated redshift classification schemes.

These multi-epoch fields and a few others from BOSS are described in more detail on the DR16 "Special Plates" website (https://sdss.org/dr16/spectro/special_plates/).

SPIDERS is one of two smaller programs conducted within eBOSS. SPIDERS was originally designed as a multi-purpose follow-up program of the Spectrum-Roentgen-Gamma (SRG)/eROSITA all-sky survey (Merloni et al. 2012; Predehl et al. 2016), with the main focus on X-ray-selected AGNs and clusters of galaxies. Given the delay in the launch of SRG (which took place in 2019 July, i.e., after the end of the main eBOSS survey observing) the program was re-purposed to target the X-ray sources from the ROSAT All-Sky Survey (RASS; Voges et al. 1999, 2000) and XMM-Newton (X-ray Multi-mirror Mission; Jansen et al. 2001), which will be eventually have their X-ray emission better characterized by eROSITA.

All SPIDERS spectra taken since the beginning of SDSS-IV have targeted either X-ray sources from the revised data reduction of ROSAT (RASS, 2RXS; Voges et al. 1999, 2000; Boller et al. 2016) and XMM-Slew (Saxton et al. 2008) catalogs, or red-sequence galaxies in clusters detected by ROSAT (part of the CODEX catalog; Finoguenov et al. 2020) or by XMM (XClass catalog; Clerc et al. 2012). We define two areas: "SPIDERS-Maximal" which corresponds to the sky area covered by an SDSS legacy or BOSS/eBOSS/SEQUELS plate, and "SPIDERS-Complete" which corresponds to the area covered by the eBOSS main survey and SEQUELS good plates. SPIDERS-Maximal (Complete) sky area amounts to 10,800 (5350) deg². The sky area corresponding to SPIDERS-Complete is shown in Figure 5.

5.3.1. SPIDERS Clusters

5.3.2. SPIDERS Target Selection Update

5.3.3. SPIDERS Galaxies and Redshifts

5.3.4. VAC: SPIDERS X-Ray Clusters Catalog for DR16

5.3.5. X-Ray Pointlike Sources

5.3.6. VACs: Multi-wavelength Properties of RASS and XMMSL AGNs

5.3.7. VAC: Spectral Properties and Black Hole Mass Estimates for SPIDERS DR16 Type 1 AGNs

5.3.8. Future Plans for SPIDERS

TDSS is the second large subprogram of eBOSS, the goal of which is to provide the first large-scale, systematic survey of spectroscopic follow-up to characterize photometric variables. TDSS makes use of the BOSS spectrographs (Smee et al. 2013), using a small fraction (about 5%) of the optical fibers on eBOSS plates. TDSS observations thus concluded with the end of the main eBOSS survey data collection 2019 March 1, and the full and final TDSS spectroscopic data are included in DR16.

There are three main components of TDSS, each now with data collection complete.

• 1.  
  The primary TDSS spectroscopic targets are selected from their variability within Pan-STARRS1 (PS1 multi-epoch imaging photometry, and/or from longer-term photometric variability between PS1 and SDSS imaging data; see, e.g., Morganson et al. 2015). TDSS single-epoch spectroscopy (Ruan et al. 2016) of these targets establishes the nature of the photometric variable (e.g., variable star versus variable quasar, and subclass, etc.), and in turn often then suggests the character of the underlying variability (e.g., pulsating RR Lyrae versus flaring late-type star versus cataclysmic variable, etc.). More than 108,000 optical spectra of these TDSS photometric variables have been observed through DR16 (in both eBOSS and the eBOSS pilot program SEQUELS). Adding in similar variables sources fortuitously already having optical spectra within the SDSS archives (from SDSS-I, -II, or -III), approximately one-third of the TDSS variables can be spectroscopically classified as variable stars, and the majority of the remaining two-thirds are variable quasars.
• 2.  
  A sample of 6500 TDSS spectroscopic fibers were allotted to obtain repeat spectra of known star and quasar subclasses of unusual and special interest, which were anticipated or suspected to exhibit spectroscopic variability in few-epoch spectroscopy (FES; see e.g., MacLeod et al. 2018). A recent specific example of this category of sources are TDSS spectra of nearly 250 dwarf carbon stars that provide strong evidence of statistical RV variations indicative of subclass binarity (Roulston et al. 2019).
• 3.  
  The more recently initiated TDSS Repeat Quasar Spectroscopy (RQS) program (see MacLeod et al. 2018) obtains multi-epoch spectra for 16,500 known quasars, sampling across a broad range of properties including redshift, luminosity, and quasar subclass type. This has a larger sample size, and also a greater homogeneity and less a priori bias to specific quasar subclasses compared to the TDSS FES program. All RQS targets have at least one earlier epoch of SDSS spectroscopy already available in the SDSS archive. The RQS program is designed especially to investigate quasar spectral variability on multi-year timescales and, in addition to its own potential for new discoveries of phenomena such as changing-look quasars or BAL variability and others, also provides a valuable (and timely) resource for planning of yet larger-scale multi-epoch quasar repeat spectral observations anticipated for the SDSS-V BHM program (see Section 7).

In total, TDSS has selected or co-selected (in the latter case, often with eBOSS quasar candidate selections) more than 131,000 spectra in SDSS-IV that probe spectroscopy in the time domain. All of these spectra are now being released in DR16.

This VAC provides measurements of resolved and total galaxy stellar masses, obtained from a low-dimensional fit to the stellar continuum: Pace et al. (2019a) document the method used to obtain the stellar continuum fit and measurements of resolved stellar mass-to-light ratio, and Pace et al. (2019b) address the aggregation into total galaxy stellar masses, including aperture-correction and accounting for foreground stars. The measurements rely on MaNGA DRP version v2_5_3, data analysis pipeline version 2.3.0, and PCAY version 1.0.0.¹⁵³ The VAC includes maps of stellar mass-to-light ratio and i-band luminosity (in solar units), a table of aperture-corrected total galaxy stellar masses, a library of synthetic model spectra, and the resulting low-dimensional basis set.

The low-dimensional basis set used to fit the stellar continuum is generated by performing principal component analysis (PCA) on a library of 40,000 synthetic SFHs: the SFHs are delayed-τ models ($\mathrm{SFR}\sim t\,{e}^{-t/\tau }$) modulated by infrequent starbursts, sharp cutoffs, and slow rejuvenations (see Pace et al. 2019a, Section 3.1.1). Broad priors dictate the possible range in stellar metallicity, attenuation by foreground dust, and uncertain phases of stellar evolution such as blue stragglers and blue horizontal branch stars (see Pace et al. 2019a, Section 3.1.2). The system of six principal component spectra ("eigenspectra") is used as a low-dimensional basis set for fitting the stellar continuum. A distribution of stellar mass-to-light ratio is obtained for each MaNGA spaxel (line of sight in a galaxy) by weighting each model spectrum's known mass-to-light ratio by its likelihood given an observed spectrum. The median of that distribution is adopted as the fiducial stellar mass-to-light ratio of a spaxel, and multiplied by the i-band luminosity to get an estimate for the stellar mass.

For DR16, i-band stellar mass-to-light ratio and i-band luminosity maps (both in solar units) are released. Stellar mass-to-light ratios have been vetted against synthetic spectra, and found to be reliable at median S/Ns, from S/N = 2–20, across a wide range of dust attenuation conditions (optical depth in the range 0–4), and across the full range of realistic stellar metallicities (−2 to +0.2 dex), with respect to solar (see Pace et al. 2019a, Section 4.10). Typical "random" uncertainties are approximately 0.1 dex (including age–metallicity degeneracies and uncertainties induced by imperfect spectrophotometry), and systematic uncertainties induced by choice of training SFHs could be as high as 0.3 dex, but are believed to be closer to 0.1–0.15 dex (see Pace et al. 2019a, Sections 4.10 and 5).

In addition to resolved maps of stellar mass-to-light ratio and i-band luminosity, the VAC includes a catalog of total stellar masses for MaNGA DR16 galaxies. We provide the total mass inside the integral field unit (IFU; after interpolating over foreground stars and other unreliable measurements with the median of its eight nearest neighbors: see Pace et al. 2019b, Section 4). We also supply two aperture corrections intended to account for mass falling outside the spatial grasp of the IFU: the first adopts the median stellar mass-to-light ratio of the outermost 0.5 effective radii, and the second (recommended) adopts a mass-to-light ratio consistent with the (g − r) color of the NSA flux minus the flux in the IFU (see Pace et al. 2019b, Section 4). A comparison of these total masses with those from the NASA-Sloan Atlas (NSA; Blanton et al. 2011) and MPA-JHU¹⁵⁴ catalog (Brinchmann et al. 2004) is shown in Figure 6.

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This catalog provides the shape asymmetry, alongside other standard galaxy morphological related measurements (CAS, Gini, M20, curve of growth radii, and Sérsic fits), based on SDSS DR7 imaging (Abazajian et al. 2009) using the eight-connected structure detection algorithm described in Pawlik et al. (2016)¹⁵⁵ to define the edges of the galaxies. We make this available for all galaxies in the MaNGA DR15 release (Aguado et al. 2019). The algorithm is specifically designed to identify faint features in the outskirts of galaxies. In this version, stars are not masked prior to creating the eight-connected binary mask, therefore stars lying within the extended light of the galaxies cause incorrect measurements. More than 10% of objects with unusual measurements have been visually inspected using Marvin and SkyServer, and the WARNINGFLAG set to 1 for the fraction of these where a star or other problem is identified. Users should not use these measurements, and additionally may wish to visually inspect small samples or outliers to ensure that the sample is appropriate for their science goals.

Starting in 2020, after SDSS-IV has ended observations at APO and LCO, the next generation of the SDSS will begin—SDSS-V (Kollmeier et al. 2017).¹⁵⁶ SDSS-V is a multi-epoch spectroscopic survey to observe nearly six million sources using the existing BOSS and APOGEE spectrographs, as well as very large swathes of interstellar medium (ISM) in the Local Group using new optical spectrographs and a suite of small telescopes. SDSS-V will operate at both APO and LCO, providing the first all-sky "panoptic" spectroscopic view of the sky, and will span a wide variety of target types and science goals.

The scientific program is divided into three "Mappers."

• 1.  
  The Milky Way Mapper (MWM) is targeting millions of stars with the APOGEE and BOSS spectrographs, ranging from the immediate solar neighborhood to the far side of the Galactic disk and the Milky Way's satellite companions. The MWM will probe the formation and evolution of the Milky way, the physics and life-cycles of its stars, and the architecture of multi-star and planetary systems.
• 2.  
  The BHM is targeting nearly half a million super-massive black holes and other X-ray sources (including newly discovered systems from the eROSITA mission) with the BOSS spectrograph in order to characterize the X-ray sky, measure black hole masses, and trace black hole growth across cosmic time.
• 3.  
  Finally, the Local Volume Mapper (LVM) employs a wide-field optical IFU and new optical spectrographs (with R ∼ 4000) to map ∼2500 deg² of sky, targeting the ISM and embedded stellar populations in the Milky Way and satellite galaxies. These maps will reveal the physics of both star formation and the interplay between these stars and the surrounding ISM.

SDSS-V builds upon the operational infrastructure and data legacy of earlier SDSS programs, with the inclusion of several key new developments. Among these are the retirement of the SDSS plug–plate system and the introduction of robotic fiber positioners in the focal planes of both 2.5 m telescopes at APO and LCO. These focal plane systems enable more efficient observing and larger target densities than achievable in previous SDSS surveys. In addition, the LVM is facilitated by the construction of several ≤1 m telescopes at one or both observatories, linked to several new optical spectrographs based on the DESI design (Martini et al. 2018). SDSS-V continues the SDSS legacy of open data policies and convenient, efficient public data access, with improved data distribution systems to serve its large, diverse, time-domain, multi-object, and integral-field data set to the world.

After 20 years of Sloan Digital Sky Surveys the data coming out from SDSS-IV in DR16 is making significant contributions to our understanding of the components our Galaxy, galaxy evolution in general, and the universe as a whole. The SDSS-IV project will end with the next data release (DR17), but the future is bright for SDSS with new technology and exciting new surveys coming in SDSS-V.