Search

Post-starburst galaxies (PSBs) are young quiescent galaxies that have recently experienced a rapid decrease in star formation, allowing us to probe the fast-quenching period of galaxy evolution. In this work, we obtained HST WFC3/F110W imaging to measure the sizes of 171 massive ($\mathrm{log(M_{*}/M_{\odot})\sim\,11)}$ spectroscopically identified PSBs at $1

We present a simple, differentiable method for predicting emission line strengths from rest-frame optical continua using an empirically-determined mapping. Extensive work has been done to develop mock galaxy catalogues that include robust predictions for galaxy photometry, but reliably predicting the strengths of emission lines has remained challenging. Our new mapping is a simple neural network implemented using the JAX Python automatic differentiation library. It is trained on Dark Energy Spectroscopic Instrument Early Release data to predict the equivalent widths (EWs) of the eight brightest optical emission lines (including H$\alpha$, H$\beta$, [O II], and [O III]) from a galaxy's rest-frame optical continuum. The predicted EW distributions are consistent with the observed ones when noise is accounted for, and we find Spearman's rank correlation coefficient $\rho_s > 0.87$ between predictions and observations for most lines. Using a non-linear dimensionality reduction technique (UMAP), we show that this is true for galaxies across the full range of observed spectral energy distributions. In addition, we find that adding measurement uncertainties to the predicted line strengths is essential for reproducing the distribution of observed line-ratios in the BPT diagram. Our trained network can easily be incorporated into a differentiable stellar population synthesis pipeline without hindering differentiability or scalability with GPUs. A synthetic catalogue generated with such a pipeline can be used to characterise and account for biases in the spectroscopic training sets used for training and calibration of photo-$z$'s, improving the modelling of systematic incompleteness for the Rubin Observatory LSST and other surveys., Comment: 17 pages, 8 figures, 1 table. Published in MNRAS

Large imaging surveys will rely on photometric redshifts (photo-z's), which are typically estimated through machine learning methods. Currently planned spectroscopic surveys will not be deep enough to produce a representative training sample for LSST, so we seek methods to improve the photo-z estimates that arise from non-representative training samples. Spectroscopic training samples for photo-z's are biased towards redder, brighter galaxies, which also tend to be at lower redshift than the typical galaxy observed by LSST, leading to poor photo-z estimates with outlier fractions nearly 4 times larger than for a representative training sample. In this paper, we apply the concept of training sample augmentation, where we augment simulated non-representative training samples with simulated galaxies possessing otherwise unrepresented features. When we select simulated galaxies with (g-z) color, i-band magnitude and redshift outside the range of the original training sample, we are able to reduce the outlier fraction of the photo-z estimates for simulated LSST data by nearly 50% and the normalized median absolute deviation (NMAD) by 56%. When compared to a fully representative training sample, augmentation can recover nearly 70% of the degradation in the outlier fraction and 80% of the degradation in NMAD. Training sample augmentation is a simple and effective way to improve training samples for photo-z's without requiring additional spectroscopic samples., Comment: 11 pages, 4 figures, published in ApJ Letters

Galaxy clusters enable unique opportunities to study cosmology, dark matter, galaxy evolution, and strongly-lensed transients. We here present a new cluster-finding algorithm, CluMPR (Clusters from Masses and Photometric Redshifts), that exploits photometric redshifts (photo-z's) as well as photometric stellar mass measurements. CluMPR uses a 2-dimensional binary search tree to search for overdensities of massive galaxies with similar redshifts on the sky and then probabilistically assigns cluster membership by accounting for photo-z uncertainties. We leverage the deep DESI Legacy Survey grzW1W2 imaging over one-third of the sky to create a catalogue of ~ 300,000 galaxy cluster candidates out to z = 1, including tabulations of member galaxies and estimates of each cluster's total stellar mass. Compared to other methods, CluMPR is particularly effective at identifying clusters at the high end of the redshift range considered (z = 0.75-1), with minimal contamination from low-mass groups. These characteristics make it ideal for identifying strongly lensed high-redshift supernovae and quasars that are powerful probes of cosmology, dark matter, and stellar astrophysics. As an example application of this cluster catalogue, we present a catalogue of candidate wide-angle strongly-lensed quasars in Appendix C. The five best candidates identified from this sample include two known lensed quasar systems and a possible changing-look lensed QSO with SDSS spectroscopy. All code and catalogues produced in this work are publicly available (see Data Availability)., Comment: 20 pages, 26 figures, submitted to MNRAS, citations added, typos fixed

The massive end of the gas-phase mass--metallicity relation (MZR) is a sensitive probe of active galactic nuclei (AGN) feedback that is a crucial but highly uncertain component of galaxy evolution models. In this paper, we extend the $z\sim0.7$ MZR by $\sim$0.5 dex up to log$(M_\star/\textrm{M}_\odot)\sim11.1$. We use extremely deep VLT VIMOS spectra from the Large Early Galaxy Astrophysics Census (LEGA-C) survey to measure metallicities for 145 galaxies. The LEGA-C MZR matches the normalization of the $z\sim0.8$ DEEP2 MZR where they overlap, so we combine the two to create an MZR spanning from 9.3 to 11.1 log$(M_\star/\textrm{M}_\odot)$. The LEGA-C+DEEP2 MZR at $z\sim0.7$ is offset to slightly lower metallicities (0.05-0.13 dex) than the $z\sim0$ MZR, but it otherwise mirrors the established power law rise at low/intermediate stellar masses and asymptotic flattening at high stellar masses. We compare the LEGA-C+DEEP2 MZR to the MZR from two cosmological simulations (IllustrisTNG and SIMBA), which predict qualitatively different metallicity trends for high-mass galaxies. This comparison highlights that our extended MZR provides a crucial observational constraint for galaxy evolution models in a mass regime where the MZR is very sensitive to choices about the implementation of AGN feedback., Comment: 10 pages, 4 figures, 1 table

In this paper, we place the Milky Way (MW) in the context of similar-looking galaxies in terms of their star-formation and chemical evolution histories. We select a sample of 138 Milky-Way analogues (MWAs) from the SDSS-IV/MaNGA survey based on their masses, Hubble types, and bulge-to-total ratios. To compare their chemical properties to the detailed spatially-resolved information available for the MW, we use a semi-analytic spectral fitting approach, which fits a self-consistent chemical-evolution and star-formation model directly to the MaNGA spectra. We model the galaxies' inner and outer regions assuming that some of the material lost in stellar winds falls inwards. We also incorporate chemical enrichment from type II and Ia supernovae to follow the alpha-element abundance at different metallicities and locations. We find some MWAs where the stellar properties closely reproduce the distribution of age, metallicity, and alpha enhancement at both small and large radii in the MW. In these systems, the match is driven by the longer timescale for star formation in the outer parts, and the inflow of enriched material to the central parts. However, other MWAs have very different histories. These divide into two categories: self-similar galaxies where the inner and outer parts evolve identically; and centrally-quenched galaxies where there is very little evidence of late-time central star formation driven by material accreted from the outer regions. We find that, although selected to be comparable, there are subtle morphological differences between galaxies in these different classes, and that the centrally-quenched galaxies formed their stars systematically earlier., Comment: 16 pages, 9 figures, MNRAS accepted version

We utilize $\sim17000$ bright Luminous Red Galaxies (LRGs) from the novel Dark Energy Spectroscopic Instrument Survey Validation spectroscopic sample, leveraging its deep ($\sim2.5$ hour/galaxy exposure time) spectra to characterize the contribution of recently quenched galaxies to the massive galaxy population at $0.41$) of our sample of recently quenched galaxies represents the largest spectroscopic sample of post-starburst galaxies at that epoch. At $0.411.2$) LRGs by measuring the fraction of stellar mass each galaxy formed in the Gyr before observation, $f_\mathrm{1 Gyr}$. Although galaxies with $f_\mathrm{1 Gyr}>0.1$ are rare at $z\sim0.4$ ($\lesssim 0.5\%$ of the population), by $z\sim0.8$ they constitute $\sim3\%$ of massive galaxies. Relaxing this threshold, we find that galaxies with $f_\mathrm{1 Gyr}>5\%$ constitute $\sim10\%$ of the massive galaxy population at $z\sim0.8$. We also identify a small but significant sample of galaxies at $z=1.1-1.3$ that formed with $f_\mathrm{1 Gyr}>50\%$, implying that they may be analogues to high-redshift quiescent galaxies that formed on similar timescales. Future analysis of this unprecedented sample promises to illuminate the physical mechanisms that drive the quenching of massive galaxies after cosmic noon., Comment: Re-uploaded after acceptance to the Astrophysical Journal Letters. 14 pages, 5 figures, comments welcome!

K-corrections, conversions between flux in observed bands to flux in rest-frame bands, are critical for comparing galaxies at various redshifts. These corrections often rely on fits to empirical or theoretical spectral energy distribution (SED) templates of galaxies. However, the templates limit reliable K-corrections to regimes where SED models are robust. For instance, the templates are not well-constrained in some bands (e.g., WISE W4), which results in ill-determined K-corrections for these bands. We address this shortcoming by developing an empirically-driven approach to K-corrections as a means to mitigate dependence on SED templates. We perform a polynomial fit for the K-correction as a function of a galaxy's rest-frame color determined in well-constrained bands (e.g., rest-frame (g-r)) and redshift, exploiting the fact that galaxy SEDs can be described as a one parameter family at low redshift (0.01 < z < 0.09). For bands well-constrained by SED templates, our empirically-driven K-corrections are comparable to the SED fitting method of Kcorrect and SED template fitting employed in the GSWLC-M2 catalogue (the updated medium-deep GALEX-SDSS-WISE Legacy Catalogue). However, our method dramatically outperforms the available SED fitting K-corrections for WISE W4. Our method also mitigates incorrect template assumptions and enforces the K-correction to be 0 at z = 0. Our K-corrected photometry and code are publicly available., Comment: 15 pages, 9 figures, submitted to MNRAS

We present the first comprehensive release of photometric redshifts (photo-z's) from the Cosmic Assembly Near-Infrared Deep Extragalactic Legacy Survey (CANDELS) team. We use statistics based upon the Quantile-Quantile (Q--Q) plot to identify biases and signatures of underestimated or overestimated errors in photo-z probability density functions (PDFs) produced by six groups in the collaboration; correcting for these effects makes the resulting PDFs better match the statistical definition of a PDF. After correcting each group's PDF, we explore three methods of combining the different groups' PDFs for a given object into a consensus curve. Two of these methods are based on identifying the minimum f-divergence curve, i.e., the PDF that is closest in aggregate to the other PDFs in a set (analogous to the median of an array of numbers). We demonstrate that these techniques yield improved results using sets of spectroscopic redshifts independent of those used to optimize PDF modifications. The best photo-z PDFs and point estimates are achieved with the minimum f-divergence using the best 4 PDFs for each object (mFDa4) and the Hierarchical Bayesian (HB4) methods, respectively. The HB4 photo-z point estimates produced $\sigma_{\rm NMAD} = 0.0227/0.0189$ and $|\Delta z/(1+z)| > 0.15$ outlier fraction = 0.067/0.019 for spectroscopic and 3D-HST redshifts, respectively. Finally, we describe the structure and provide guidance for the use of the CANDELS photo-z catalogs, which are available at https://archive.stsci.edu/hlsp/candels., Comment: 35 pages, 19 figures, published in ApJ, data available at https://archive.stsci.edu/hlsp/candels

Uncertainty quantification is crucial for assessing the predictive ability of AI algorithms. Much research has been devoted to describing the predictive distribution (PD) $F(y|\mathbf{x})$ of a target variable $y \in \mathbb{R}$ given complex input features $\mathbf{x} \in \mathcal{X}$. However, off-the-shelf PDs (from, e.g., normalizing flows and Bayesian neural networks) often lack conditional calibration with the probability of occurrence of an event given input $\mathbf{x}$ being significantly different from the predicted probability. Current calibration methods do not fully assess and enforce conditionally calibrated PDs. Here we propose \texttt{Cal-PIT}, a method that addresses both PD diagnostics and recalibration by learning a single probability-probability map from calibration data. The key idea is to regress probability integral transform scores against $\mathbf{x}$. The estimated regression provides interpretable diagnostics of conditional coverage across the feature space. The same regression function morphs the misspecified PD to a re-calibrated PD for all $\mathbf{x}$. We benchmark our corrected prediction bands (a by-product of corrected PDs) against oracle bands and state-of-the-art predictive inference algorithms for synthetic data. We also provide results for two applications: (i) probabilistic nowcasting given sequences of satellite images, and (ii) conditional density estimation of galaxy distances given imaging data (so-called photometric redshift estimation). Our code is available as a Python package https://github.com/lee-group-cmu/Cal-PIT ., Comment: 21 pages, 11 figures. Under review. Code available as a Python package https://github.com/lee-group-cmu/Cal-PIT

We analyze spatially resolved and co-added SDSS-IV MaNGA spectra with signal-to-noise ~100 from 2200 passive central galaxies (z~0.05) to understand how central galaxy assembly depends on stellar mass (M*) and halo mass (Mh). We control for systematic errors in Mh by employing a new group catalog from Tinker (2020a,b) and the widely-used Yang et al. (2007) catalog. At fixed M*, the strength of several stellar absorption features varies systematically with Mh. Completely model-free, this is one of the first indications that the stellar populations of centrals with identical M* are affected by the properties of their host halos. To interpret these variations, we applied full spectral fitting with the code alf. At fixed M*, centrals in more massive halos are older, show lower [Fe/H], and have higher [Mg/Fe] with 3.5 sigma confidence. We conclude that halos not only dictate how much M* galaxies assemble, but also modulate their chemical enrichment histories. Turning to our analysis at fixed Mh, high-M* centrals are older, show lower [Fe/H], and have higher [Mg/Fe] for Mh>10^{12}Msun/h with confidence > 4 sigma. While massive passive galaxies are thought to form early and rapidly, our results are among the first to distinguish these trends at fixed Mh. They suggest that high-M* centrals experienced unique early formation histories, either through enhanced collapse and gas fueling, or because their halos were early-forming and highly concentrated, a possible signal of galaxy assembly bias., Comment: Accepted for publication in ApJ. 28 pages and 12 figures

We present, for the first time, the relationship between local stellar mass surface density, $\mathrm{\Sigma_{*}}$, and N/O derived from SDSS-IV MaNGA data, using a sample of $792765$ high signal-to-noise ratio star-forming spaxels. Using a combination of phenomenological modelling and partial correlation analysis, we find that $\mathrm{\Sigma_{*}}$ alone is insufficient to predict the N/O in MaNGA spaxels, and that there is an additional dependence on the local star formation rate surface density, $\mathrm{\Sigma_{SFR}}$. This effect is a factor of $3$ stronger than the dependence of 12+log(O/H) on $\mathrm{\Sigma_{SFR}}$. Surprisingly, we find that the local N/O scaling relations also depend on the total galaxy stellar mass at fixed $\Sigma_{*}$ as well as the galaxy size at fixed stellar mass. We find that more compact galaxies are more nitrogen rich, even when $\mathrm{\Sigma_{*}}$ and $\mathrm{\Sigma_{SFR}}$ are controlled for. We show that $\sim50\%$ of the variance of N/O is explained by the total stellar mass and size. Thus, the evolution of nitrogen in galaxies is set by more than just local effects and does not simply track the build up of oxygen in galaxies. The precise form of the N/O-O/H relation is therefore sensitive to the sample of galaxies from which it is derived. This result casts doubt on the universal applicability of nitrogen-based strong-line metallicity indicators derived in the local universe., Comment: 22 pages, 14 figures. Accepted for publication in the Astrophysical Journal

Studies of cosmology, galaxy evolution, and astronomical transients with current and next-generation wide-field imaging surveys like the Rubin Observatory Legacy Survey of Space and Time (LSST) are all critically dependent on estimates of photometric redshifts. Capsule networks are a new type of neural network architecture that is better suited for identifying morphological features of the input images than traditional convolutional neural networks. We use a deep capsule network trained on $ugriz$ images, spectroscopic redshifts, and Galaxy Zoo spiral/elliptical classifications of $\sim$400,000 Sloan Digital Sky Survey (SDSS) galaxies to do photometric redshift estimation. We achieve a photometric redshift prediction accuracy and a fraction of catastrophic outliers that are comparable to or better than current methods for SDSS main galaxy sample-like data sets ($r\leq17.8$ and $z_{\mathrm{spec}}\leq0.4$) while requiring less data and fewer trainable parameters. Furthermore, the decision-making of our capsule network is much more easily interpretable as capsules act as a low-dimensional encoding of the image. When the capsules are projected on a 2-dimensional manifold, they form a single redshift sequence with the fraction of spirals in a region exhibiting a gradient roughly perpendicular to the redshift sequence. We perturb encodings of real galaxy images in this low-dimensional space to create synthetic galaxy images that demonstrate the image properties (e.g., size, orientation, and surface brightness) encoded by each dimension. We also measure correlations between galaxy properties (e.g., magnitudes, colours, and stellar mass) and each capsule dimension. We publicly release our code, estimated redshifts, and additional catalogues at https://biprateep.github.io/encapZulate-1 ., Comment: 22 pages, 12 figures. Published in MNRAS

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 (MaStar) 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 (APOGEE-2) survey which publicly releases infra-red spectra of over 650,000 stars. The main sample from the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), as well as the sub-survey Time Domain Spectroscopic Survey (TDSS) data were fully released in DR16. New single-fiber optical spectroscopy released in DR17 is from the SPectroscipic IDentification of ERosita Survey (SPIDERS) sub-survey and the eBOSS-RM program. Along with the primary data sets, DR17 includes 25 new or updated Value Added Catalogs (VACs). 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 (MWM), Local Volume Mapper (LVM) and Black Hole Mapper (BHM) surveys., Comment: 40 pages, 8 figures, 6 tables. In press at ApJSS (arxiv v2 corrects some minor typos and updates references)

Many astrophysical analyses depend on estimates of redshifts (a proxy for distance) determined from photometric (i.e., imaging) data alone. Inaccurate estimates of photometric redshift uncertainties can result in large systematic errors. However, probability distribution outputs from many photometric redshift methods do not follow the frequentist definition of a Probability Density Function (PDF) for redshift -- i.e., the fraction of times the true redshift falls between two limits $z_{1}$ and $z_{2}$ should be equal to the integral of the PDF between these limits. Previous works have used the global distribution of Probability Integral Transform (PIT) values to re-calibrate PDFs, but offsetting inaccuracies in different regions of feature space can conspire to limit the efficacy of the method. We leverage a recently developed regression technique that characterizes the local PIT distribution at any location in feature space to perform a local re-calibration of photometric redshift PDFs. Though we focus on an example from astrophysics, our method can produce PDFs which are calibrated at all locations in feature space for any use case., Comment: Fourth Workshop on Machine Learning and the Physical Sciences (NeurIPS 2021)

Improving our knowledge of global Milky Way (MW) properties is critical for connecting the detailed measurements only possible from within our Galaxy to our understanding of the broader galaxy population. We train Gaussian Process Regression (GPR) models on SDSS galaxies to map from galaxy properties (stellar mass, apparent axis ratio, star formation rate, bulge-to-total ratio, disk scale length, and bar vote fraction) to UV (GALEX $FUV/NUV$), optical (SDSS $ugriz$) and IR (2MASS $JHKs$ and WISE $W1/W2/W3/W4$) fluxes and uncertainties. With these models we estimate the photometric properties of the MW, resulting in a full UV-to-IR spectral energy distribution (SED) as it would be measured externally, viewed face-on. We confirm that the Milky Way lies in the green valley in optical diagnostic diagrams, but show for the first time that the MW is in the star-forming region in standard UV and IR diagnostics -- characteristic of the population of red spiral galaxies. Although our GPR method predicts one band at a time, the resulting MW UV--IR SED is consistent with SEDs of local spirals with characteristics broadly similar to the MW, suggesting that these independent predictions can be combined reliably. Our UV--IR SED will be invaluable for reconstructing the MW's star formation history using the same tools employed for external galaxies, allowing comparisons of results from \textit{in situ} measurements to those from the methods used for extra-galactic objects., Comment: 23 pages, 11 figures, 4 appendices, 31 pages total, published in Monthly Notices of the Royal Astronomical Society

We derive ages, metallicities, and individual element abundances of early- and late-type galaxies (ETGs and LTGs) out to 1.5 R$_e$. We study a large sample of 1900 galaxies spanning $8.6 - 11.3 \log M/M_{\odot}$ in stellar mass, through key absorption features in stacked spectra from the SDSS-IV/MaNGA survey. We use mock galaxy spectra with extended star formation histories to validate our method for LTGs and use corrections to convert the derived ages into luminosity- and mass-weighted quantities. We find flat age and negative metallicity gradients for ETGs and negative age and negative metallicity gradients for LTGs. Age gradients in LTGs steepen with increasing galaxy mass, from $-0.05\pm0.11~\log$ Gyr/R$_e$ for the lowest mass galaxies to $-0.82\pm0.08~\log$ Gyr/R$_e$ for the highest mass ones. This strong gradient-mass relation has a slope of $-0.70\pm0.18$. Comparing local age and metallicity gradients with the velocity dispersion $\sigma$ within galaxies against the global relation with $\sigma$ shows that internal processes regulate metallicity in ETGs but not age, and vice versa for LTGs. We further find that metallicity gradients with respect to local $\sigma$ show a much stronger dependence on galaxy mass than radial metallicity gradients. Both galaxy types display flat [C/Fe] and [Mg/Fe], and negative [Na/Fe] gradients, whereas only LTGs display gradients in [Ca/Fe] and [Ti/Fe]. ETGs have increasingly steep [Na/Fe] gradients with local $\sigma$ reaching $6.50\pm0.78$ dex/$\log$ km/s for the highest masses. [Na/Fe] ratios are correlated with metallicity for both galaxy types across the entire mass range in our sample, providing support for metallicity dependent supernova yields., Comment: 21 pages, 21 figures, 4 tables + Appendix

While all models for the evolution of galaxies require the accretion of gas to sustain their growth via on-going star formation, it has proven difficult to directly detect this inflowing material. In this paper we use data of nearby star-forming galaxies in the SDSS IV Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey to search for evidence of accretion imprinted in the chemical composition of the interstellar medium. We measure both the O/H and N/O abundance ratios in regions previously identified as having anomalously low values of O/H. We show that the unusual locations of these regions in the N/O vs. O/H plane indicate that they have been created through the mixing of disk gas having higher metallicity with accreted gas having lower metallicity. Taken together with previous analysis on these anomalously low-metallicity regions, these results imply that accretion of metal-poor gas can probably sustain star formation in present-day late-type galaxies., Comment: 13 pages, 8 figures, accepted for publication in The Astrophysical Journal

We use the statistical power of the MaNGA integral-field spectroscopic galaxy survey to improve the definition of strong line diagnostic boundaries used to classify gas ionization properties in galaxies. We detect line emission from 3.6 million spaxels distributed across 7400 individual galaxies spanning a wide range of stellar masses, star formation rates, and morphological types, and find that the gas-phase velocity dispersion sigma_HAlpha correlates strongly with traditional optical emission line ratios such as [S II]/HAlpha, [N II]/HAlpha, [O I]/HAlpha, and [O III]/HBeta. Spaxels whose line ratios are most consistent with ionization by galactic HII regions exhibit a narrow range of dynamically cold line of sight velocity distributions (LOSVDs) peaked around 25 km/s corresponding to a galactic thin disk, while those consistent with ionization by active galactic nuclei (AGN) and low-ionization emission-line regions (LI(N)ERs) have significantly broader LOSVDs extending to 200 km/s. Star-forming, AGN, and LI(N)ER regions are additionally well separated from each other in terms of their stellar velocity dispersion, stellar population age, HAlpha equivalent width, and typical radius within a given galaxy. We use our observations to revise the traditional emission line diagnostic classifications so that they reliably identify distinct dynamical samples both in two-dimensional representations of the diagnostic line ratio space and in a multi-dimensional space that accounts for the complex folding of the star forming model surface. By comparing the MaNGA observations to the SDSS single-fiber galaxy sample we note that the latter is systematically biased against young, low metallicity star-forming regions that lie outside of the 3 arcsec fiber footprint., Comment: 23 pages, 16 figures. Revised version accepted for publication in ApJ, updates all results to MaNGA final data release DR17

Bars inhabit the majority of local-Universe disk galaxies and may be important drivers of galaxy evolution through the redistribution of gas and angular momentum within disks. We investigate the star formation and gas properties of bars in galaxies spanning a wide range of masses, environments, and star formation rates using the MaNGA galaxy survey. Using a robustly-defined sample of 684 barred galaxies, we find that fractional (or scaled) bar length correlates with the host's offset from the star-formation main sequence. Considering the morphology of the H$\alpha$ emission we separate barred galaxies into different categories, including barred, ringed, and central configurations, together with H$\alpha$ detected at the ends of a bar. We find that only low-mass galaxies host star formation along their bars, and that this is located predominantly at the leading edge of the bar itself. Our results are supported by recent simulations of massive galaxies, which show that the position of star formation within a bar is regulated by a combination of shear forces, turbulence and gas flows. We conclude that the physical properties of a bar are mostly governed by the existing stellar mass of the host galaxy, but that they also play an important role in the galaxy's ongoing star formation., Comment: 14 pages, 6 figures, accepted for publication in MNRAS

Dust attenuation in star-forming spiral galaxies affects stars and gas in different ways due to local variations in dust geometry. We present spatially resolved measurements of dust attenuation for a sample of 232 such star-forming spiral galaxies, derived from spectra acquired by the SDSS-IV MaNGA survey. The dust attenuation affecting the stellar populations of these galaxies (obtained using full spectrum stellar population fitting methods) is compared with the dust attenuation in the gas (derived from the Balmer decrement). Both of these attenuation measures increase for local regions of galaxies with higher star formation rates; the dust attenuation affecting the stellar populations increases more so than the dust attenuation in the gas, causing the ratio of the dust attenuation affecting the stellar populations to the dust attenuation in the gas to decrease for local regions of galaxies with higher star formation rate densities. No systematic difference is discernible in any of these dust attenuation quantities between the spiral arm and inter-arm regions of the galaxies. While both the dust attenuation in the gas and the dust attenuation affecting the stellar populations decrease with galactocentric radius, the ratio of the two quantities does not vary with radius. This ratio does, however, decrease systematically as the stellar mass of the galaxy increases. Analysis of the radial profiles of the two dust attenuation measures suggests that there is a disproportionately high concentration of birth clouds (incorporating gas, young stars and clumpy dust) nearer to the centres of star-forming spiral galaxies., Comment: 17 pages, 8 figures, accepted for publication in Monthly Notices of the Royal Astronomical Society

This paper documents the sixteenth data release (DR16) from the Sloan Digital Sky Surveys; the fourth and penultimate from the fourth phase (SDSS-IV). This is the first release of data from the southern hemisphere survey of the Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2); new data from APOGEE-2 North are also included. DR16 is also notable as the final data release for the main cosmological program of the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), and all raw and reduced spectra from that project are released here. DR16 also includes all the data from the Time Domain Spectroscopic Survey (TDSS) and new data from the SPectroscopic IDentification of ERosita Survey (SPIDERS) programs, both of which were co-observed on eBOSS plates. DR16 has no new data from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey (or the MaNGA Stellar Library "MaStar"). We also preview future SDSS-V operations (due to start in 2020), and summarize plans for the final SDSS-IV data release (DR17)., Comment: DR16 release: Monday Dec 9th 2019. This is the alphabetical order SDSS-IV collaboration data release paper. 25 pages, 6 figures, accepted by ApJS on 11th May 2020. Minor changes clarify or improve text and figures relative to v1

In this paper we use strong line calibrations of N/O and O/H in MaNGA spaxel data to explore the systematics introduced by variations in N/O on various strong-line metallicity diagnostics. We find radial variations in N/O at fixed O/H which correlate with total galaxy stellar-mass; and which can induce $\sim 40 \%$ systematic uncertainties in oxygen abundance gradients when nitrogen-dependent abundance calibrations are used. Empirically, we find that these differences are associated with variation in the local star formation efficiency, as predicted by recent chemical evolution models for galaxies, but we cannot rule out other processes such as radial migration and the accretion of passive dwarf galaxies also playing a role., Comment: 8 pages, 4 figures. Submitted to ApJL. All comments are welcome

Classification of intermediate redshift ($z$ = 0.3--0.8) emission line galaxies as star-forming galaxies, composite galaxies, active galactic nuclei (AGN), or low-ionization nuclear emission regions (LINERs) using optical spectra alone was impossible because the lines used for standard optical diagnostic diagrams: [NII], H$\alpha$, and [SII] are redshifted out of the observed wavelength range. In this work, we address this problem using four supervised machine learning classification algorithms: $k$-nearest neighbors (KNN), support vector classifier (SVC), random forest (RF), and a multi-layer perceptron (MLP) neural network. For input features, we use properties that can be measured from optical galaxy spectra out to $z < 0.8$---[OIII]/H$\beta$, [OII]/H$\beta$, [OIII] line width, and stellar velocity dispersion---and four colors ($u-g$, $g-r$, $r-i$, and $i-z$) corrected to $z=0.1$. The labels for the low redshift emission line galaxy training set are determined using standard optical diagnostic diagrams. RF has the best area under curve (AUC) score for classifying all four galaxy types, meaning highest distinguishing power. Both the AUC scores and accuracies of the other algorithms are ordered as MLP$>$SVC$>$KNN. The classification accuracies with all eight features (and the four spectroscopically-determined features only) are 93.4% (92.3%) for star-forming galaxies, 69.4% (63.7%) for composite galaxies, 71.8% (67.3%) for AGNs, and 65.7% (60.8%) for LINERs. The stacked spectrum of galaxies of the same type as determined by optical diagnostic diagrams at low redshift and RF at intermediate redshift are broadly consistent. Our publicly available code (https://github.com/zkdtc/MLC_ELGs) and trained models will be instrumental for classifying emission line galaxies in upcoming wide-field spectroscopic surveys., Comment: 14 pages, 14 figures, accepted for publication on ApJ

The late assembly of massive galaxies is thought to be dominated by stellar accretion in their outskirts (beyond 2 effective radii Re) due to dry, minor galaxy mergers. We use observations of 1010 passive early-type galaxies (ETGs) within z<0.15 from SDSS IV MaNGA to search for evidence of this accretion. The outputs from the stellar population fitting codes FIREFLY, pPXF, and Prospector are compared to control for systematic errors in stellar metallicity (Z) estimation. We find that the average radial logZ/Zsun profiles of ETGs in various stellar mass (M) bins are not linear. As a result, these profiles are poorly characterized by a single gradient value, explaining why weak trends reported in previous work can be difficult to interpret. Instead, we examine the full radial extent of stellar metallicity profiles and find them to flatten in the outskirts of M>10^{11}Msun ETGs. This is a signature of stellar accretion. Based on a toy model for stellar metallicity profiles, we infer the ex-situ stellar mass fraction in ETGs as a function of M and galactocentric radius. We find that ex-situ stars at 2Re make up 20% of the projected stellar mass of M<10^{10.5}Msun ETGs, rising up to 80% for M>10^{11.5}Msun ETGs., Comment: Accepted for publication in ApJ. 13 pages, 6 figures. Fixed date of acceptance

We investigate the resolved relation between local extinction and star formation surface density within nearby star-forming galaxies selected from the MaNGA survey. Balmer decrement measurements imply an extinction of the H{\alpha} line emission which scales approximately linearly with the logarithm of the star formation surface density: $ A_{H{\alpha}} = 0.46 \log(\Sigma_{SFR}) + 1.53$. Secondary dependencies are observed such that, at a given $\Sigma_{SFR}$, regions of lower metallicity and/or enhanced H{\alpha} equivalent width (EW) suffer less obscuration than regions of higher metallicity and/or lower H{\alpha} EW. Spaxels lying above the mean relation also tend to belong to galaxies that are more massive, larger and viewed under higher inclination than average. We present a simple model in which the observed trends can be accounted for by a metallicity-dependent scaling between $\Sigma_{SFR}$ and $\Sigma_{dust}$ via a super-linear Kennicutt-Schmidt relation ($n_{KS} \sim 1.47$) and a dust-to-gas ratio which scales linearly with metallicity (DGR($Z_{\odot}$) = 0.01). The relation between the resulting total dust column and observed effective extinction towards nebular regions requires a geometry for the relative distribution of H{\alpha} emitting regions and dust that deviates from a uniform foreground screen and also from an entirely homogeneous mixture of dust and emitting sources. The best-fit model features an H{\alpha} EW and galactocentric distance dependent fraction of the dust mass in a clumpy foreground screen in front of a homogeneous mixture., Comment: Accepted for publication in ApJ. Figures 2 and 3 show the observed star formation - extinction relation. Figures 9 and 10 show our favored model

Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) is acquiring integral-field spectroscopy for the largest sample of galaxies to date. By 2020, the MaNGA Survey --- one of three core programs in the fourth-generation Sloan Digital Sky Survey (SDSS-IV) --- will have observed a statistically representative sample of 10$^4$ galaxies in the local Universe ($z\lesssim0.15$). In addition to a robust data-reduction pipeline (DRP), MaNGA has developed a data-analysis pipeline (DAP) that provides higher-level data products. To accompany the first public release of its code base and data products, we provide an overview of the MaNGA DAP, including its software design, workflow, measurement procedures and algorithms, performance, and output data model. In conjunction with our companion paper Belfiore et al., we also assess the DAP output provided for 4718 observations of 4648 unique galaxies in the recent SDSS Data Release 15 (DR15). These analysis products focus on measurements that are close to the data and require minimal model-based assumptions. Namely, we provide stellar kinematics (velocity and velocity dispersion), emission-line properties (kinematics, fluxes, and equivalent widths), and spectral indices (e.g., D4000 and the Lick indices). We find that the DAP provides robust measurements and errors for the vast majority ($>$99%) of analyzed spectra. We summarize assessments of the precision and accuracy of our measurements as a function of signal-to-noise, and provide specific guidance to users regarding the limitations of the data. The MaNGA DAP software is publicly available and we encourage community involvement in its development., Comment: 70 pages, 34 figures; AJ in press; see also Belfiore et al. 2019, AJ, 158, 160 (arXiv:1901.00866)

We use data from 1222 late-type star-forming galaxies in the SDSS IV MaNGA survey to identify regions in which the gas-phase metallicity is anomalously-low compared to expectations from the tight empirical relation between metallicity and stellar surface mass-density at a given stellar mass. We find anomalously low metallicity (ALM) gas in 10% of the star-forming spaxels, and in 25% of the galaxies in the sample. The incidence rate of ALM gas increases strongly with both global and local measures of the specific star-formation rate, and is higher in lower mass galaxies and in the outer regions of galaxies. The incidence rate is also significantly higher in morphologically disturbed galaxies. We estimate that the lifetimes of the ALM regions are a few hundred Myr. We argue that the ALM gas has been delivered to its present location by a combination of interactions, mergers, and accretion from the halo, and that this infusion of gas stimulates star-formation. Given the estimated lifetime and duty cycle of such events, we estimate that the time-averaged accretion rate of ALM gas is similar to the star-formation rate in late type galaxies over the mass-range M$_* \sim10^9$ to 10$^{10}$ M$_{\odot}$., Comment: Accepted by ApJ

The Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey, one of three core programs of the fourth-generation Sloan Digital Sky Survey (SDSS-IV), is producing a massive, high-dimensional integral field spectroscopic data set. However, leveraging the MaNGA data set to address key questions about galaxy formation presents serious data-related challenges due to the combination of its spatially inter-connected measurements and sheer volume. For each galaxy, the MaNGA pipelines produce relatively large data files to preserve the spatial correlations of the spectra and measurements, but this comes at the expense of storing the data set in a coarsely-chunked manner. The coarse chunking and total volume of the data make it time-consuming to download and curate locally-stored data. Thus, accessing, querying, visually exploring, and performing statistical analyses across the whole data set at a fine-grained scale is extremely challenging using just FITS files. To overcome these challenges, we have developed \marvin: a toolkit consisting of a Python package, Application Programming Interface (API), and web application utilizing a remote database. \marvin's robust and sustainable design minimizes maintenance, while facilitating user-contributed extensions such as high level analysis code. Finally, we are in the process of abstracting out \marvin's core functionality into a separate product so that it can serve as a foundation for others to develop \marvin-like systems for new science applications., Comment: 26 pages, 14 figures

Twenty years have passed since first light for the Sloan Digital Sky Survey (SDSS). Here, we release data taken by the fourth phase of SDSS (SDSS-IV) across its first three years of operation (July 2014-July 2017). This is the third data release for SDSS-IV, and the fifteenth from SDSS (Data Release Fifteen; DR15). New data come from MaNGA - we release 4824 datacubes, as well as the first stellar spectra in the MaNGA Stellar Library (MaStar), the first set of survey-supported analysis products (e.g. stellar and gas kinematics, emission line, and other maps) from the MaNGA Data Analysis Pipeline (DAP), and a new data visualisation and access tool we call "Marvin". The next data release, DR16, will include new data from both APOGEE-2 and eBOSS; those surveys release no new data here, but we document updates and corrections to their data processing pipelines. The release is cumulative; it also includes the most recent reductions and calibrations of all data taken by SDSS since first light. In this paper we describe the location and format of the data and tools and cite technical references describing how it was obtained and processed. The SDSS website (www.sdss.org) has also been updated, providing links to data downloads, tutorials and examples of data use. While SDSS-IV will continue to collect astronomical data until 2020, and will be followed by SDSS-V (2020-2025), we end this paper by describing plans to ensure the sustainability of the SDSS data archive for many years beyond the collection of data., Comment: Paper to accompany DR15. 25 pages, 6 figures. Accepted for publication in ApJSS. The two papers on the MaNGA Data Analysis Pipeline (DAP, Westfall et al. and Belfiore et al., see Section 4.1.2), and the paper on Marvin (Cherinka et al., see Section 4.2) have been submitted for collaboration review and will be posted to arXiv in due course. v2 fixes some broken URLs in the PDF

Chemical enrichment signatures strongly constrain galaxy formation and evolution, and a detailed understanding of abundance patterns provides clues regarding the nucleosynthetic production pathways of elements. Using the SDSS-IV MaNGA IFU survey, we study radial gradients of chemical element abundances in detail. We use stacked spectra out to 1 Re of 366 early-type galaxies with masses 9.9 - 10.8 log $M/M_{\odot}$ to probe the abundances of the elements C, N, Na, Mg, Ca, and Ti, relative to the abundance of Fe, by fitting stellar population models to a combination of Lick absorption indices. We find that C, Mg, and Ti trace each other both as a function of galaxy radius and galaxy mass. These similar C and Mg abundances within and across galaxies set a lower limit for star-formation timescales. Conversely, N and Ca are generally offset to lower abundances. The under-abundance of Ca compared to Mg implies delayed enrichment of Ca through Type Ia supernovae, whereas the correlated behaviour of Ti and the lighter $\alpha$ elements, C and Mg, suggest contributions to Ti from Type II supernovae. We obtain shallow radial gradients in [Mg/Fe], [C/Fe], and [Ti/Fe], meaning that these inferences are independent of radius. However, we measure strong negative radial gradients for [N/Fe] and [Na/Fe], of up to $-0.25\pm0.05$ and $-0.29\pm0.02$ dex/Re respectively. These gradients become shallower with decreasing galaxy mass. We find that N and Na abundances increase more steeply with velocity dispersion within galaxies than globally, while the other elements show the same relation locally and globally. This implies that the high Na and N abundances found in massive early type galaxies are generated by internal processes within galaxies. These are strongly correlated with the total metallicity, suggesting metallicity-dependent Na enrichment, and secondary N production in massive early-type galaxies., Comment: 17 pages, 9 figures, 4 tables. MNRAS in press

MaNGA provides the opportunity to make precise spatially resolved measurements of the IMF slope in galaxies owing to its unique combination of spatial resolution, wavelength coverage and sample size. We derive radial gradients in age, element abundances and IMF slope analysing optical and near-infrared absorption features from stacked spectra out to the half-light radius of 366 early-type galaxies with masses $9.9 - 10.8\;\log M/M_{\odot}$. We find flat gradients in age and [$\alpha$/Fe] ratio, as well as negative gradients in metallicity, consistent with the literature. We further derive significant negative gradients in the [Na/Fe] ratio with galaxy centres being well enhanced in Na abundance by up to 0.5 dex. Finally, we find a gradient in IMF slope with a bottom-heavy IMF in the centre (typical mass excess factor of 1.5) and a Milky Way-type IMF at the half-light radius. This pattern is mass-dependent with the lowest mass galaxies in our sample featuring only a shallow gradient around a Milky Way IMF. Our results imply the local IMF-$\sigma$ relation within galaxies to be even steeper than the global relation and hint towards the local metallicity being the dominating factor behind the IMF variations. We also employ different stellar population models in our analysis and show that a radial IMF gradient is found independently of the stellar population model used. A similar analysis of the Wing-Ford band provides inconsistent results and further evidence of the difficulty in measuring and modelling this particular feature., Comment: 28 pages, 24 figures, 9 tables. MNRAS in press

We present a catalogue of 38 spectroscopically detected strong galaxy-galaxy gravitational lens candidates identified in the Sloan Digital Sky Survey IV (SDSS-IV). We were able to simulate narrow-band images for 8 of them demonstrating evidence of multiple images. Two of our systems are compound lens candidates, each with 2 background source-planes. One of these compound systems shows clear lensing features in the narrow-band image. Our sample is based on 2812 galaxies observed by the Mapping Nearby Galaxies at APO (MaNGA) integral field unit (IFU). This Spectroscopic Identification of Lensing Objects (SILO) survey extends the methodology of the Sloan Lens ACS Survey (SLACS) and BOSS Emission-Line Survey (BELLS) to lower redshift and multiple IFU spectra. We searched ~ 1.5 million spectra, of which 3065 contained multiple high signal-to-noise background emission-lines or a resolved [OII] doublet, that are included in this catalogue. Upon manual inspection, we discovered regions with multiple spectra containing background emission-lines at the same redshift, providing evidence of a common source-plane geometry which was not possible in previous SLACS and BELLS discovery programs. We estimate more than half of our candidates have an Einstein radius > 1.7", which is significantly greater than seen in SLACS and BELLS. These larger Einstein radii produce more extended images of the background galaxy increasing the probability that a background emission-line will enter one of the IFU spectroscopic fibres, making detection more likely., Comment: Accepted for publication in MNRAS, March 8, 2018. In press. 16 pages, 5 figures, 4 tables

In this paper, we investigate 2727 galaxies observed by MaNGA as of June 2016 to develop spatially resolved techniques for identifying signatures of active galactic nuclei (AGN). We identify 303 AGN candidates. The additional spatial dimension imposes challenges in identifying AGN due to contamination from diffuse ionized gas, extra-planar gas and photoionization by hot stars. We show that the combination of spatially-resolved line diagnostic diagrams and additional cuts on H$\alpha$ surface brighness and H$\alpha$ equivalent width can distinguish between AGN-like signatures and high-metallicity galaxies with LINER-like spectra. Low mass galaxies with high specific star formation rates are particularly difficult to diagnose and routinely show diagnostic line ratios outside of the standard star-formation locus. We develop a new diagnostic -- the distance from the standard diagnostic line in the line-ratios space -- to evaluate the significance of the deviation from the star-formation locus. We find 173 galaxies that would not have been selected as AGN candidates based on single-fibre spectral measurements but exhibit photoionization signatures suggestive of AGN activity in the MaNGA resolved observations, underscoring the power of large integral field unit (IFU) surveys. A complete census of these new AGN candidates is necessary to understand their nature and probe the complex co-evolution of supermassive black holes and their hosts., Comment: 18 pages, 11 figures, accepted to MNRAS

We present new evidence for AGN feedback in a subset of 69 quenched low-mass galaxies ($M_{\star} \lesssim 5\times10^{9}$ M$_{\odot}$, $M_{\rm{r}} > -19$) selected from the first two years of the SDSS-IV MaNGA survey. The majority (85 per cent) of these quenched galaxies appear to reside in a group environment. We find 6 galaxies in our sample that appear to have an active AGN that is preventing on-going star-formation; this is the first time such a feedback mechanism has been observed in this mass range. Interestingly, five of these six galaxies have an ionised gas component that is kinematically offset from their stellar component, suggesting the gas is either recently accreted or outflowing. We hypothesise these six galaxies are low-mass equivalents to the "red geysers" observed in more massive galaxies. Of the other 63 galaxies in the sample, we find 8 do appear for have some low-level, residual star formation, or emission from hot, evolved stars. The remaining galaxies in our sample have no detectable ionised gas emission throughout their structures, consistent with them being quenched. This work shows the potential for understanding the detailed physical properties of dwarf galaxies through spatially resolved spectroscopy., Comment: 20 pages, 11 figures, accepted for publication in MNRAS

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since July 2014. This paper describes the second data release from this phase, and the fourteenth from SDSS overall (making this, Data Release Fourteen or DR14). This release makes public data taken by SDSS-IV in its first two years of operation (July 2014-2016). Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the first phase began operations in 2000. New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey (eBOSS); the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data driven machine learning algorithm known as "The Cannon"; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scientific use. The SDSS website (www.sdss.org) has been updated for this release, and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020, and will be followed by SDSS-V., Comment: SDSS-IV collaboration alphabetical author data release paper. DR14 happened on 31st July 2017. 19 pages, 5 figures. Accepted by ApJS on 28th Nov 2017 (this is the "post-print" and "post-proofs" version; minor corrections only from v1, and most of errors found in proofs corrected)

We utilize elemental-abundance information for Galactic red giant stars in five open clusters (NGC 7789, NGC 6819, M67, NGC 188, and NGC 6791) from the Apache Point Observatory Galactic Evolution Experiment (APOGEE) DR13 dataset to age-date the chemical evolution of the high- and low-$\alpha$ element sequences of the Milky Way. Key to this time-stamping is the cluster NGC 6791, whose stellar members have mean abundances that place it in the high-$\alpha$, high-[Fe/H] region of the [$\alpha$/Fe]-[Fe/H] plane. Based on the cluster's age ($\sim 8$ Gyr), Galactocentric radius, and height above the Galactic plane, as well as comparable chemistry reported for APOGEE stars in Baade's Window, we suggest that the two most likely origins for NGC 6791 are as an original part of the thick-disk, or as a former member of the Galactic bulge. Moreover, because NGC 6791 lies at the \textit{high metallicity end} ([Fe/H] $\sim 0.4$) of the high-$\alpha$ sequence, the age of NGC 6791 places a limit on the \textit{youngest age} of stars in the high-metallicity, high-$\alpha$ sequence for the cluster's parent population (i.e., either the bulge or the disk). In a similar way, we can also use the age and chemistry of NGC 188 to set a limit of $\sim 7$ Gyr on the \textit{oldest age} of the low-$\alpha$ sequence of the Milky Way. Therefore, NGC 6791 and NGC 188 are potentially a pair of star clusters that bracket both the timing and the duration of an important transition point in the chemical history of the Milky Way., Comment: 15 pages, 6 figures, 2 tables; Accepted for Publication in ApJ

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) began observations in July 2014. It pursues three core programs: APOGEE-2, MaNGA, and eBOSS. In addition, eBOSS contains two major subprograms: TDSS and SPIDERS. This paper describes the first data release from SDSS-IV, Data Release 13 (DR13), which contains new data, reanalysis of existing data sets and, like all SDSS data releases, is inclusive of previously released data. DR13 makes publicly available 1390 spatially resolved integral field unit observations of nearby galaxies from MaNGA, the first data released from this survey. It includes new observations from eBOSS, completing SEQUELS. In addition to targeting galaxies and quasars, SEQUELS also targeted variability-selected objects from TDSS and X-ray selected objects from SPIDERS. DR13 includes new reductions of the SDSS-III BOSS data, improving the spectrophotometric calibration and redshift classification. DR13 releases new reductions of the APOGEE-1 data from SDSS-III, with abundances of elements not previously included and improved stellar parameters for dwarf stars and cooler stars. For the SDSS imaging data, DR13 provides new, more robust and precise photometric calibrations. Several value-added catalogs are being released in tandem with DR13, in particular target catalogs relevant for eBOSS, TDSS, and SPIDERS, and an updated red-clump catalog for APOGEE. This paper describes the location and format of the data now publicly available, as well as providing references to the important technical papers that describe the targeting, observing, and data reduction. The SDSS website, http://www.sdss.org, provides links to the data, tutorials and examples of data access, and extensive documentation of the reduction and analysis procedures. DR13 is the first of a scheduled set that will contain new data and analyses from the planned ~6-year operations of SDSS-IV., Comment: Full information on DR13 available at http://www.sdss.org. Comments welcome to spokesperson@sdss.org. To be published in ApJS

Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) is an optical fiber-bundle integral-field unit (IFU) spectroscopic survey that is one of three core programs in the fourth-generation Sloan Digital Sky Survey (SDSS-IV). With a spectral coverage of 3622 - 10,354 Angstroms and an average footprint of ~ 500 arcsec^2 per IFU the scientific data products derived from MaNGA will permit exploration of the internal structure of a statistically large sample of 10,000 low redshift galaxies in unprecedented detail. Comprising 174 individually pluggable science and calibration IFUs with a near-constant data stream, MaNGA is expected to obtain ~ 100 million raw-frame spectra and ~ 10 million reduced galaxy spectra over the six-year lifetime of the survey. In this contribution, we describe the MaNGA Data Reduction Pipeline (DRP) algorithms and centralized metadata framework that produces sky-subtracted, spectrophotometrically calibrated spectra and rectified 3-D data cubes that combine individual dithered observations. For the 1390 galaxy data cubes released in Summer 2016 as part of SDSS-IV Data Release 13 (DR13), we demonstrate that the MaNGA data have nearly Poisson-limited sky subtraction shortward of ~ 8500 Angstroms and reach a typical 10-sigma limiting continuum surface brightness mu = 23.5 AB/arcsec^2 in a five arcsec diameter aperture in the g band. The wavelength calibration of the MaNGA data is accurate to 5 km/s rms, with a median spatial resolution of 2.54 arcsec FWHM (1.8 kpc at the median redshift of 0.037) and a median spectral resolution of sigma = 72 km/s., Comment: 37 pages, 22 figures. Accepted for publication in AJ. v2 updates arXiv reference to Yan+16b, v3 fixes some embedded DR13 links. Version with full resolution figures is available at http://www.stsci.edu/~dlaw/Papers/MaNGA_Data.pdf