We compare predictions of how active galactic nuclei (AGNs) populate host galaxies at low redshifts to observations, finding large discrepancies between cosmological simulation predictions and observed patterns. Modern cosmological simulations include AGN feedback models tuned to reproduce the observed galaxy stellar mass function. However, due to a lack of real understanding of the physics of AGN feedback, these models vary significantly across simulations. To distinguish between the models and potentially test the underlying physics, we carry out independent tests of these models. In an earlier study, we found that F-AGN-the observed completeness-corrected fraction of galaxies hosting radio AGNs with an Eddington ratio lambda > 10(-3)-to be a strong function of host-galaxy stellar mass (M star) but nearly independent of host specific star formation rates (sSFRs) at fixed M-star. In this study, we test the radio mode AGN feedback models of the EAGLE, SIMBA, and TNG100 simulations by comparing their predictions of FAGNM star to our observational constraint. We find that none of these simulations even qualitatively reproduce the observed dependencies of F-AGN on M-star and sSFR. Finally, we find that although the given TNG100 model could be modified in order to better reproduce the observed F-AGN trend, this modification would likely also change its prediction for the local stellar mass function and star formation rates-key observations used for calibrating the simulation in the first place. Our findings highlight a pressing need to revisit the AGN feedback prescriptions in EAGLE, SIMBA, TNG100, and other similar models.

We present an algorithmic method for efficiently planning a long-term, large-scale multiobject spectroscopy program. The Sloan Digital Sky Survey V (SDSS-V) Focal Plane System performs multiobject spectroscopy using 500 robotic positioners to place fibers feeding optical and infrared spectrographs across a wide field. SDSS-V uses this system to observe targets throughout the year at two observatories in support of the science goals of its Milky Way Mapper and Black Hole Mapper programs. These science goals require observations of objects over time with preferred temporal spacings (referred to as “cadences”), which can differ from object to object even in the same area of sky. robostrategy is the software we use to construct our planned observations so that they can best achieve the desired goals given the time available as a function of sky brightness and local sidereal time, and to assign fibers to targets during specific observations. We use linear programming techniques to seek optimal allocations of time under the constraints given. We present the methods and example results obtained with this software.

Mapping the local and distant Universe is key to our understanding of it. For decades, the Sloan Digital Sky Survey (SDSS) has made a concerted effort to map millions of celestial objects to constrain the physical processes that govern our Universe. The most recent and fifth generation of SDSS (SDSS-V) is organized into three scientific "mappers": the Milky Way Mapper, which aims to chart the various components of the Milky Way and constrain its formation and assembly; the Black Hole Mapper, which focuses on understanding supermassive black holes in distant galaxies across the Universe; and the Local Volume Mapper, which uses integral field spectroscopy to map the ionized interstellar medium in the Local Group. This paper describes the scope and content for the nineteenth data release (DR19) of SDSS, which is the most substantial to date in SDSS-V. DR19 is the first to contain data from all three mappers. Additionally, we also describe nine value-added catalogs that enhance the science that can be conducted with the SDSS-V data. Finally, we discuss how to access SDSS DR19 and provide illustrative examples and tutorials.

The Sloan Digital Sky Survey V (SDSS-V) is pioneering panoptic spectroscopy: it is the first all-sky, multiepoch, optical-to-infrared spectroscopic survey. SDSS-V is mapping the sky with multiobject spectroscopy (MOS) at telescopes in both hemispheres (the 2.5 m Sloan Foundation Telescope at Apache Point Observatory and the 100-inch du Pont Telescope at Las Campanas Observatory), where 500 zonal robotic fiber positioners feed light from a wide-field focal plane to an optical (R similar to 2000, 500 fibers) and a near-infrared (R similar to 22,000, 300 fibers) spectrograph. In addition to these MOS capabilities, the survey is pioneering ultra-wide-field (similar to 4000 deg(2)) integral field spectroscopy enabled by a new dedicated facility (LVM-I) at Las Campanas Observatory, where an integral field spectrograph (IFS) with 1801 lenslet-coupled fibers arranged in a 0 degrees.5-diameter hexagon feeds multiple R similar to 4000 optical spectrographs that cover 3600-9800 angstrom. SDSS-V's hardware and multiyear survey strategy are designed to decode the chemodynamical history of the Milky Way and tackle fundamental open issues in stellar physics in its Milky Way Mapper program, trace the growth physics of supermassive black holes in its Black Hole Mapper program, and understand the self-regulation mechanisms and the chemical enrichment of galactic ecosystems at the energy injection scale in its Local Volume Mapper program. The survey is well timed to multiply the scientific output from major all-sky space missions. The SDSS-V MOS programs began robotic operations in 2021; IFS observations began in 2023 with the completion of the LVM-I facility. SDSS-V builds on decades of heritage of SDSS's pioneering advances in data analysis, collaboration spirit, infrastructure, and product deliverables in astronomy.

The evolutionary history of the Milky Way disk is imprinted in the ages, positions, and chemical compositions of individual stars. In this study, we derive the intrinsic density distribution of different stellar populations using the final data release of the Apache Point Observatory Galactic Evolution Experiment (APOGEE) survey. A total of 203,197 red giant branch stars are used to sort the stellar disk (R <= 20 kpc) into subpopulations of metallicity (Delta[M/H] = 0.1 dex), age ( Delta log(ageyr)=0.1 ), and alpha-element abundances ([alpha/M]). We fit the present-day structural parameters and density distribution of each stellar subpopulation after correcting for the survey selection function. The low-alpha disk is characterized by longer scale lengths and shorter scale heights, and is best fit by a broken exponential radial profile for each population. The high-alpha disk is characterized by shorter scale lengths and larger scale heights, and is generally well-approximated by a single exponential radial profile. These results are applied to produce new estimates of the integrated properties of the Milky Way from early times to the present day. We measure the total stellar mass of the disk to be 5.27-1.5+0.2x1010 M circle dot, and the average mass-weighted scale length is Rd = 2.37 +/- 0.2 kpc. The Milky Way's present-day color of (g - r) = 0.72 +/- 0.02 is consistent with the classification of a red spiral galaxy, although it has only been in the "green valley" region of the galaxy color-mass diagram for the last similar to 3 Gyr.

The radial velocity catalog from the Apache Point Observatory Galactic Evolution Experiment (APOGEE) is unique in its simultaneously large volume and high precision as a result of its decade-long survey duration, multiplexing (600 fibers), and spectral resolution of R ∼ 22,500. However, previous data reductions of APOGEE have not fully realized the potential radial velocity (RV) precision of the instrument. Here we present an RV catalog based on a new reduction of all 2.6 million visits of APOGEE DR17 and validate it against improved estimates for the theoretical RV performance. The core ideas of the new reduction are the simultaneous modeling of all components in the spectra, rather than a separate subtraction of point estimates for the sky, and a marginalization over stellar types, rather than a grid search for an optimum. We show that this catalog, when restricted to RVs measured with the same fiber, achieves noise-limited precision down to 30 m s −1 and delivers well-calibrated uncertainties. We also introduce a general method for calibrating fiber-to-fiber constant RV offsets and demonstrate its importance for high RV precision work in multifiber spectrographs. After calibration, we achieve 47 m s −1 RV precision on the combined catalog with RVs measured with different fibers. This degradation in precision relative to measurements with only a single fiber suggests that refining line spread function models should be a focus in the Sloan Digital Sky Survey V to improve the fiber-unified RV catalog.

One crucial aspect of planning any large scale astronomical survey is constructing an observing strategy that maximizes reduced data quality. This is especially important for surveys that are rather heterogeneous and broad-ranging in their science goals. The Sloan Digital Sky Survey V (SDSS-V), which now utilizes the Focal Plane System (FPS) to robotically place fibers that feed the spectrographs, certainly meets these criteria. The addition of the FPS facilitates an increase in survey efficiency, number of targets, and target diversity, but also means the positions of fibers must be constrained to allow for simultaneous observations of sometimes competing programs. The constraints on the positions of the fibers are clearly driven by properties of the science targets, e.g., the type of target, brightness of the target, position of the target relative to others in the field, etc. The parameters used to describe these constraints will also depend on the intended science goal of the observation, which will vary with the types of objects requested for the particular observation and the planned sky conditions for the observation. In this work, we detail the SDSS-V data collection scenarios, which consist of sets of parameters that serve as the framework for constraining fiber placements. The numerical values of these parameters were set based on either past experiences or from a series of new tests, which we describe in detail here. These parameters allow a survey like SDSS-V to be algorithmically planned to maximize the science output, while guaranteeing data quality throughout its operation.

We present one of the largest uniform optical spectroscopic surveys of X-ray selected sources to date that were observed as a pilot study for the Black Hole Mapper (BHM) survey. The BHM program of the Sloan Digital Sky Survey (SDSS)-V is designed to provide optical spectra for hundreds of thousands of X-ray selected sources from the SRG/eROSITA all-sky survey. This significantly improves our ability to classify and characterise the physical properties of large statistical populations of X-ray emitting objects. Our sample consists of 13 079 sources in the eROSITA eFEDS performance verification field, 12 011 of which provide reliable redshifts from 0 less than or similar to z <= 5.8. The vast majority of these objects were detected as point-like sources (X-ray flux limit F0.5 - 2 keV greater than or similar to 6.5 x 10(-15) erg/s/cm(2)) and were observed for about 20 years with fibre-fed SDSS spectrographs. After including all available redshift information for the eFEDS sources from the dedicated SDSS-V plate programme and archival data, we visually inspected the SDSS optical spectra to verify the reliability of these redshift measurements and the performance of the SDSS pipeline. The visual inspection allowed us to recover reliable redshifts (for 99% of the spectra with a signal-to-noise ratio of > 2) and to assign classes to the sources, and we confirm that the vast majority of our sample consists of active galactic nuclei (AGNs). Only similar to 3% of the eFEDS/SDSS sources are Galactic objects. We analysed the completeness and purity of the spectroscopic redshift catalogue, in which the spectroscopic completeness increases from 48% (full sample) to 81% for a cleaner, brighter (r(AB) < 21.38) sample that we defined by considering a high X-ray detection likelihood, a reliable counterpart association, and an optimal sky coverage. We also show the diversity of the optical spectra of the X-ray selected AGNs and provide spectral stacks with a high signal-to-noise ratio in various sub-samples with different redshift and optical broad-band colours. Our AGN sample contains optical spectra of (broad-line) quasars, narrow-line galaxies, and optically passive galaxies. It is considerably diverse in its colours and in its levels of nuclear obscuration.

We examine the demographics of radio-emitting active galactic nuclei (AGN) in the local universe as a function of host galaxy properties, most notably both stellar mass and star formation rate. Radio AGN activity is theoretically implicated in helping reduce star formation rates of galaxies, and therefore it is natural to investigate the relationship between these two galaxy properties. We use a sample of around 10, 000 galaxies from the Mapping Nearby Galaxies at APO (MaNGA) survey, part of the Sloan Digital Sky Survey IV (SDSS-IV), along with the Faint Images of the Radio Sky at Twenty centimeters (FIRST) radio survey and the National Radio Astronomy Observatory (NRAO) Very Large Array (VLA) Sky Survey (NVSS). There are 1,126 galaxies in MaNGA with radio detections. Using star formation rate and stellar mass estimates based on Pipe3D, inferred from the high signal-to-noise ratio measurements from MaNGA, we show that star formation rates are strongly correlated with 20 cm radio emission, as expected. We identify as radio AGN those radio emitters that are much stronger than expected from the star formation rate. Using this sample of AGN, the well-measured stellar velocity dispersions from MaNGA, and the black hole M-sigma relationship, we examine the Eddington ratio distribution and its dependence on stellar mass and star formation rate. We find that the Eddington ratio distribution depends strongly on stellar mass, with more massive galaxies having larger Eddington ratios. As found in previous studies, the AGN fraction increases rapidly with stellar mass. We do not find any dependence on star formation rate, specific star formation rate, or velocity dispersion when controlling for stellar mass. We conclude that galaxy star formation rates appear to be unrelated to the presence or absence of a radio AGN, which may be useful in constraining theoretical models of AGN feedback.

The radial velocity catalog from the Apache Point Observatory Galactic Evolution Experiment (APOGEE) is unique in its simultaneously large volume and high precision as a result of its decade-long survey duration, multiplexing (600 fibers), and spectral resolution of R ∼ 22,500. However, previous data reductions of APOGEE have not fully realized the potential radial velocity (RV) precision of the instrument. Here we present an RV catalog based on a new reduction of all 2.6 million visits of APOGEE DR17 and validate it against improved estimates for the theoretical RV performance. The core ideas of the new reduction are the simultaneous modeling of all components in the spectra, rather than a separate subtraction of point estimates for the sky, and a marginalization over stellar types, rather than a grid search for an optimum. We show that this catalog, when restricted to RVs measured with the same fiber, achieves noise-limited precision down to 30 m/s and delivers well-calibrated uncertainties. We also introduce a general method for calibrating fiber-to-fiber constant RV offsets and demonstrate its importance for high RV precision work in multi-fiber spectrographs. After calibration, we achieve 47 m/s RV precision on the combined catalog with RVs measured with different fibers. This degradation in precision relative to measurements with only a single fiber suggests that refining line spread function models should be a focus in SDSS-V to improve the fiber-unified RV catalog.

The new Focal Plane Systems (FPS) built for the fifth iteration of the Sloan Digital Sky Survey (SDSS-V) at Las Campanas Observatory and Apache Point Observatory each consist of 500 robotic fiber positioners, feeding optical and infrared multi-object spectrographs, that can be arranged in configurations, internally called "designs", to match science targets in the night sky. SDSS-V plans to observe roughly 50,000 of these designs over the 5 year survey, with up to 30 being observed on a single night at each observatory. Besides the sheer volume of designs, there are strict time domain requirements ("cadences") that must be respected in order to complete the signature SDSS time domain surveys. This complex set of requirements necessitates software that can ensure cadence requirements are always respected, in addition to normal observing requirements such as maximum skybrightness, moon distance, etc., while also optimizing the designs scheduled in a night to ensure all designs are completed by the end of the survey. We present an overview of the roboscheduler package which was developed to solve these problems.

We examine the demographics of radio-emitting active galactic nuclei (AGN) in the local Universe as a function of host galaxy properties, most notably both stellar mass (M-star) and star formation rate (SFR). Radio AGN activity is theoretically implicated in helping reduce the SFR of galaxies, and therefore it is natural to investigate the relationship between these two galaxy properties. We use the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) optical IFU catalog in conjunction with the NVSS and Faint Images of the Radio Sky at Twenty radio catalogs. MaNGA's high precision determinations of SFR allow us to impose a clean cut to reliably identify radio AGN from star formers. Using this sample of AGN, the well-measured stellar velocity dispersions from MaNGA, and the black hole M-sigma relationship, we examine the Eddington ratio distribution (ERD) and its dependence on M-star and SFR. We find that the ERD depends strongly on M-star, with more massive galaxies having larger Eddington ratios (lambda). Interpreting our model fit to the data leads to a completeness-corrected estimate of F-AGN(lambda > 0.001), the fraction of galaxies with radio AGN with lambda > 0.001. At log(M-star/M-circle dot)similar to 11, we estimate F-AGN = 0.02. The AGN fraction increases rapidly with M-star, and at log(M-star/M-circle dot)similar to 12, we estimate F-AGN similar to 0.24. We do not find any dependence on SFR, specific star formation rate, or velocity dispersion when controlling for stellar mass. We conclude that galaxy SFRs appear to be unrelated to the presence or absence of a radio AGN, which may be useful in constraining theoretical models of AGN feedback.

We present a new, all-sky quasar catalog, Quaia, that samples the largest comoving volume of any existing spectroscopic quasar sample. The catalog draws on the 6,649,162 quasar candidates identified by the Gaia mission that have redshift estimates from the space observatory's low-resolution BP/RP spectra. This initial sample is highly homogeneous and complete, but has low purity, and 18% of even the bright ($G<20.0$) confirmed quasars have discrepant redshift estimates ($|\Delta z/(1+z)|>0.2$) compared to those from the Sloan Digital Sky Survey (SDSS). In this work, we combine the Gaia candidates with unWISE infrared data (based on the Wide-field Infrared Survey Explorer survey) to construct a catalog useful for cosmological and astrophysical quasar studies. We apply cuts based on proper motions and Gaia and unWISE colors, reducing the number of contaminants by $\sim$4$\times$. We improve the redshifts by training a $k$-nearest neighbors model on SDSS redshifts, and achieve estimates on the $G<20.0$ sample with only 6% (10%) catastrophic errors with $|\Delta z/(1+z)|>0.2$ ($0.1$), a reduction of $\sim$3$\times$ ($\sim$2$\times$) compared to the Gaia redshifts. The final catalog has 1,295,502 quasars with $G<20.5$, and 755,850 candidates in an even cleaner $G<20.0$ sample, with accompanying rigorous selection function models. We compare Quaia to existing quasar catalogs, showing that its large effective volume makes it a highly competitive sample for cosmological large-scale structure analyses. The catalog is publicly available at https://zenodo.org/records/10403370.

We use mid-infrared variability in galaxies to search for active galactic nuclei (AGN) in the local universe. We use a sample of 10,220 galaxies from the Mapping Nearby Galaxies at Apache Point Observatory survey, part of the Sloan Digital Sky Survey. For each galaxy, we examine its mid-infrared variability in the W2 [4.6 mu m] band over 13 years using data from the Wide Infrared Survey Explorer (WISE) All-Sky and Near Earth Objects WISE missions. We demonstrate that we can detect variability signatures as small as about 7% in the rms variation of W2 flux for the majority of cases. Using other AGN signatures of the variable galaxies, such as optical narrow lines, optical broad lines, and WISE W1 - W2 colors, we show that similar to 75% of the variables show these additional AGN signatures, indicating that the bulk of these cases are likely to be AGN. We also identify seven galaxies that have light curves characteristic of tidal disruption events. We present here a publicly available catalog of the light-curve variability in W2 of these galaxies.

We use simulated galaxy observations from the NIHAO-SKIRT-Catalog to test the accuracy of spectral energy distribution (SED) modeling techniques. SED modeling is an essential tool for inferring star formation histories from nearby galaxy observations but is fraught with difficulty due to our incomplete understanding of stellar populations, chemical enrichment processes, and the nonlinear, geometry-dependent effects of dust. The NIHAO-SKIRT-Catalog uses hydrodynamic simulations and radiative transfer to produce SEDs from the ultraviolet (UV) through the infrared (IR), accounting for dust. We use the commonly used Prospector software to perform inference on these SEDs and compare the inferred stellar masses and star formation rates (SFRs) to the known values in the simulation. We match the stellar population models to isolate the effects of differences in the star formation history, the chemical evolution history, and the dust. For the high-mass NIHAO galaxies (>10(9.5 )M( circle dot)), we find that model mismatches lead to inferred SFRs that are on average underestimated by a factor of 2 when fit to UV through IR photometry, and a factor of 3 when fit to UV through optical photometry. These biases lead to significant inaccuracies in the resulting specific SFR-mass relations, with UV through optical fits showing particularly strong deviations from the true relation of the simulated galaxies. In the context of massive existing and upcoming photometric surveys, these results highlight that star formation history inference from photometry may remain imprecise and inaccurate and that there is a pressing need for more realistic testing of existing techniques.

We use simulated galaxy observations from the NIHAO-SKIRT-Catalog to test the accuracy of Spectral Energy Distribution (SED) modeling techniques. SED modeling is an essential tool for inferring star-formation histories from nearby galaxy observations, but is fraught with difficulty due to our incomplete understanding of stellar populations, chemical enrichment processes, and the nonlinear, geometry-dependent effects of dust on our observations. The NIHAO-SKIRT-Catalog uses hydrodynamic simulations and radiative transfer to produce SEDs from the ultraviolet (UV) through the infrared (IR), accounting for the effects of dust. We use the commonly used Prospector software to perform inference on these SEDs, and compare the inferred stellar masses and star-formation rates (SFRs) to the known values in the simulation. We match the stellar population models to isolate the effects of differences in the star-formation history, the chemical evolution history, and the dust. We find that the combined effect of model mismatches for high mass (> 10^9.5 M_⊙) galaxies leads to inferred SFRs that are on average underestimated by a factor of 2 when fit to UV through IR photometry, and a factor of 3 when fit to UV through optical photometry. These biases lead to significant inaccuracies in the resulting sSFR-mass relations, with UV through optical fits showing particularly strong deviations from the true relation of the simulated galaxies. In the context of massive existing and upcoming photometric surveys, these results highlight that star-formation history inference from photometry remains imprecise and inaccurate, and that there is a pressing need for more realistic testing of existing techniques.

We use simulated attenuation curves from the NIHAO-SKIRT-Catalog to test the flexibility of commonly used dust attenuation models in the face of the variations expected from realistic star-dust geometries. Motivated by lack of flexibility in these existing models, we propose a novel dust attenuation model with three free parameters that can accurately recover the simulated attenuation curves as well as the best-fitting curves from the commonly used models. This new model is fully analytic and treats all starlight equally, in contrast to two-component dust attenuation models. We use the parameterization to investigate the relationship between the overall attenuation law shape and the strength of the 2175 & Aring; bump. Our results indicate variation in star-dust geometry leads these features to correlate tightly, with grayer attenuation curves having weaker bumps.

The astronomical community is grappling with the increasing volume and complexity of data produced by modern telescopes, due to difficulties in reducing, accessing, analyzing, and combining archives of data. To address this challenge, we propose the establishment of a coordinating body, an "entity," with the specific mission of enhancing the interoperability, archiving, distribution, and production of both astronomical data and software. This report is the culmination of a workshop held in February 2023 on the Future of Astronomical Data Infrastructure. Attended by 70 scientists and software professionals from ground-based and space-based missions and archives spanning the entire spectrum of astronomical research, the group deliberated on the prevailing state of software and data infrastructure in astronomy, identified pressing issues, and explored potential solutions. In this report, we describe the ecosystem of astronomical data, its existing flaws, and the many gaps, duplication, inconsistencies, barriers to access, drags on productivity, missed opportunities, and risks to the long-term integrity of essential data sets. We also highlight the successes and failures in a set of deep dives into several different illustrative components of the ecosystem, included as an appendix.