This paper documents the seventeenth data release (DR17) from the Sloan Digital Sky Surveys; the fifth and final release from the fourth phase (SDSS-IV). DR17 contains the complete release of the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey, which reached its goal of surveying over 10,000 nearby galaxies. The complete release of the MaNGA Stellar Library accompanies this data, providing observations of almost 30,000 stars through the MaNGA instrument during bright time. DR17 also contains the complete release of the Apache Point Observatory Galactic Evolution Experiment 2 survey that publicly releases infrared spectra of over 650,000 stars. The main sample from the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), as well as the subsurvey Time Domain Spectroscopic Survey data were fully released in DR16. New single-fiber optical spectroscopy released in DR17 is from the SPectroscipic IDentification of ERosita Survey subsurvey and the eBOSS-RM program. Along with the primary data sets, DR17 includes 25 new or updated value-added catalogs. This paper concludes the release of SDSS-IV survey data. SDSS continues into its fifth phase with observations already underway for the Milky Way Mapper, Local Volume Mapper, and Black Hole Mapper surveys.

The Sloan Extension for Galactic Understanding and Exploration 2 (SEGUE-2) obtained 128,288 low-resolution spectra (R ∼ 1800) of 118,958 unique stars in the first year of the Sloan Digital Sky Survey III (2008–2009). SEGUE-2 targeted prioritized distant halo tracers (blue horizontal-branch stars, K giants, and M giants) and metal-poor or kinematically hot populations. The main goal of SEGUE-2 was to target stars in the distant halo and measure their kinematics and chemical abundances to learn about the formation and evolution of the Milky Way. We present the SEGUE-2 field placement and target selection strategies. We discuss the success rate of the targeting based on the SEGUE-2 spectra and other spectroscopic and astrometric surveys. We describe the final SEGUE-2/SDSS-III improvements to the stellar parameter determinations based on the SEGUE Stellar Parameter Pipeline. We report a (g − i) color−effective temperature relation calibrated to the IRFM. We evaluate the accuracy and uncertainties associated with these stellar parameters by comparing with fundamental parameters, a sample of high-resolution spectra of SEGUE stars analyzed homogeneously, stars in well-studied clusters, and stars observed in common by the APOGEE survey. The final SEGUE spectra, calibration data, and derived parameters described here were released in SDSS-III Data Release 9 and continue to be included in all subsequent SDSS Data Releases. Because of its faint limiting magnitude and emphasis on the distant halo, the public SEGUE-2 data remain an important resource for the spectroscopy of stars in the Milky Way.

The eighteenth data release (DR18) of the Sloan Digital Sky Survey (SDSS) is the first one for SDSS-V, the fifth generation of the survey. SDSS-V comprises three primary scientific programs or “Mappers”: the Milky Way Mapper (MWM), the Black Hole Mapper (BHM), and the Local Volume Mapper. This data release contains extensive targeting information for the two multiobject spectroscopy programs (MWM and BHM), including input catalogs and selection functions for their numerous scientific objectives. We describe the production of the targeting databases and their calibration and scientifically focused components. DR18 also includes ∼25,000 new SDSS spectra and supplemental information for X-ray sources identified by eROSITA in its eFEDS field. We present updates to some of the SDSS software pipelines and preview changes anticipated for DR19. We also describe three value-added catalogs (VACs) based on SDSS-IV data that have been published since DR17, and one VAC based on the SDSS-V data in the eFEDS field.

Robotic fiber positioner (RFP) arrays are becoming heavily adopted in wide-field massively multiplexed spectroscopic survey instruments. RFP arrays decrease nightly operational overheads through rapid reconfiguration between fields and exposures. In comparison to similar instruments, SDSS-V has selected a very dense RFP packing scheme where any point in a field is typically accessible to three or more robots. This design provides flexibility in target assignment. However, the task of collisionless trajectory planning is especially challenging. We present two multiagent distributed control strategies that are highly efficient and computationally inexpensive for determining collision-free paths for RFPs in heavily overlapping workspaces. We demonstrate that a reconfiguration path between two arbitrary robot configurations can be efficiently found if a “folded” state, in which all robot arms are retracted and aligned in a lattice-like orientation, is inserted between the initial and final states. Although developed for SDSS-V, the approach we describe is generic and thus applicable to a wide range of RFP designs and layouts. Robotic fiber positioner technology continues to advance rapidly, and in the near future ultra-densely packed RFP designs may be feasible. Our algorithms are especially capable in routing paths in very crowded environments, where we see efficient results even in regimes significantly more crowded than the SDSS-V RFP design.