The spectral analysis and data products in Data Release 16 (DR16; 2019 December) from the high-resolution near-infrared Apache Point Observatory Galactic Evolution Experiment (APOGEE)-2/Sloan Digital Sky Survey (SDSS)-IV survey are described. Compared to the previous APOGEE data release (DR14; 2017 July), APOGEE DR16 includes about 200000 new stellar spectra, of which 100000 are from a new southern APOGEE instrument mounted on the 2.5m du Pont telescope at Las Campanas Observatory in Chile. DR16 includes all data taken up to 2018 August, including data released in previous data releases. All of the data have been re-reduced and re-analyzed using the latest pipelines, resulting in a total of 473307 spectra of 437445 stars. Changes to the analysis methods for this release include, but are not limited to, the use of MARCS model atmospheres for calculation of the entire main grid of synthetic spectra used in the analysis, a new method for filling "holes" in the grids due to unconverged model atmospheres, and a new scheme for continuum normalization. Abundances of the neutron-capture element Ce are included for the first time. A new scheme for estimating uncertainties of the derived quantities using stars with multiple observations has been applied, and calibrated values of surface gravities for dwarf stars are now supplied. Compared to DR14, the radial velocities derived for this release more closely match those in the Gaia DR2 database, and a clear improvement in the spectral analysis of the coolest giants can be seen.
The second generation of the Apache Point Observatory Galactic Evolution Experiment (APOGEE-2) observes the "archaeological" record embedded in hundreds of thousands of stars to explore the assembly history and evolution of the Milky Way Galaxy. APOGEE-2 maps the dynamical and chemical patterns of Milky Way stars with data from the 1-meter NMSU Telescope and the 2.5-meter Sloan Foundation Telescope at the Apache Point Observatory in New Mexico (APOGEE-2N), and the 2.5-meter du Pont Telescope at Las Campanas Observatory in Chile (APOGEE-2S).
Multi-epoch radial velocity measurements of stars can be used to identify stellar, substellar, and planetary-mass companions. Even a small number of observation epochs can be informative about companions, though there can be multiple qualitatively different orbital solutions that fit the data. We have custom-built a Monte Carlo sampler (The Joker) that delivers reliable (and often highly multimodal) posterior samplings for companion orbital parameters given sparse radial velocity data. Here we use The Joker to perform a search for companions to 96231 red giant stars observed in the APOGEE survey (DR14) with >=3 spectroscopic epochs. We select stars with probable companions by making a cut on our posterior belief about the amplitude of the variation in stellar radial velocity induced by the orbit. We provide (1) a catalog of 320 companions for which the stellar companion's properties can be confidently determined, (2) a catalog of 4898 stars that likely have companions, but would require more observations to uniquely determine the orbital properties, and (3) posterior samplings for the full orbital parameters for all stars in the parent sample. We show the characteristics of systems with confidently determined companion properties and highlight interesting systems with candidate compact object companions.
The volume of data generated by astronomical surveys is growing rapidly. Traditional analysis techniques in spectroscopy either demand intensive human interaction or are computationally expensive. In this scenario, machine learning, and unsupervised clustering algorithms in particular, offer interesting alternatives. The Apache Point Observatory Galactic Evolution Experiment (APOGEE) offers a vast data set of near-infrared stellar spectra, which is perfect for testing such alternatives. Our research applies an unsupervised classification scheme based on K-means to the massive APOGEE data set. We explore whether the data are amenable to classification into discrete classes. We apply the K-means algorithm to 153,847 high resolution spectra (R~22,500). We discuss the main virtues and weaknesses of the algorithm, as well as our choice of parameters. We show that a classification based on normalised spectra captures the variations in stellar atmospheric parameters, chemical abundances, and rotational velocity, among other factors. The algorithm is able to separate the bulge and halo populations, and distinguish dwarfs, sub-giants, RC, and RGB stars. However, a discrete classification in flux space does not result in a neat organisation in the parameters' space. Furthermore, the lack of obvious groups in flux space causes the results to be fairly sensitive to the initialisation, and disrupts the efficiency of commonly-used methods to select the optimal number of clusters. Our classification is publicly available, including extensive online material associated with the APOGEE Data Release 12 (DR12). Our description of the APOGEE database can help greatly with the identification of specific types of targets for various applications. We find a lack of obvious groups in flux space, and identify limitations of the K-means algorithm in dealing with this kind of data.
We use models of stellar angular momentum evolution to determine ages for ~500 stars in the APOGEE-Kepler Cool Dwarfs sample. We focus on lower-main-sequence stars, where other age-dating tools become ineffective. Our age distributions are compared to those derived from asteroseismic and giant samples and solar analogs. We are able to recover gyrochronological ages for old, lower-main-sequence stars, a remarkable improvement over prior work in hotter stars. Under our model assumptions, our ages have a median relative uncertainty of 14%, comparable to the age precision inferred for more massive stars using traditional methods. We investigate trends of Galactic {alpha}-enhancement with age, finding evidence of a detection threshold between the age of the oldest {alpha}-poor stars and that of the bulk {alpha}-rich population. We argue that gyrochronology is an effective tool reaching ages of 10-12Gyr in K and early M dwarfs. Finally, we present the first effort to quantify the impact of detailed abundance patterns on rotational evolution. We estimate a ~15% bias in age for cool, {alpha}-enhanced (+0.4dex) stars when standard solar-abundance-pattern rotational models are used for age inference, rather than models that appropriately account for {alpha}-enrichment.
The APOGEE survey has obtained high-resolution infrared spectra of more than 100,000 stars. Deriving chemical abundances patterns of these stars is paramount to piecing together the structure of the MilkyWay. While the derived chemical abundances have been shown to be precise for most stars, some calibration problems have been reported, in particular for more metal-poor stars. In this paper, we aim to (1) re-determine the chemical abundances of the APOGEE+Kepler stellar sample (APOKASC) with an independent procedure, line list and line selection, and high-quality surface gravity information from asteroseismology, and (2) extend the abundance catalogue by including abundances that are not currently reported in the most recent APOGEE release (DR12). We fixed the Teff and logg to those determined using spectrophotometric and asteroseismic techniques, respectively. We made use of the Brussels Automatic Stellar Parameter (BACCHUS) code to derive the metallicity and broadening parameters for the APOKASC sample. In addition, we derived differential abundances with respect to Arcturus.
We present the stellar kinematics across the Galactic bulge and into the disk at positive longitudes from the SDSS-III APOGEE spectroscopic survey of the Milky Way. APOGEE includes extensive coverage of the stellar populations of the bulge along the midplane and near-plane regions. From these data, we have produced kinematic maps of 10000 stars across longitudes of 0{deg}<l<65{deg}, and primarily across latitudes of |b|<5{deg} in the bulge region. The APOGEE data reveal that the bulge is cylindrically rotating across all latitudes and is kinematically hottest at the very center of the bulge, with the smallest gradients in both kinematic and chemical space inside the innermost region (|l,b|)<(5{deg},5{deg}). The results from APOGEE show good agreement with data from other surveys at higher latitudes and a remarkable similarity to the rotation and dispersion maps of barred galaxies viewed edge-on. The thin bar that is reported to be present in the inner disk within a narrow latitude range of |b|<2{deg} appears to have a corresponding signature in [Fe/H] and [{alpha}/Fe]. Stars with [Fe/H]>-0.5 have dispersion and rotation profiles that are similar to that of N-body models of boxy/peanut bulges. There is a smooth kinematic transition from the thin bar and boxy bulge (|l,b|)<(15{deg},12{deg}) out to the disk for stars with [Fe/H]>-1.0, and the chemodynamics across (l,b) suggests that the stars in the inner Galaxy with [Fe/H]>-1.0 originate in the disk.
We are carrying out a large ancillary program with the Sloan Digital Sky Survey, SDSS-III, using the fiber-fed multi-object near-infrared APOGEE spectrograph, to obtain high-resolution H-band spectra of more than 1200 M dwarfs. These observations will be used to measure spectroscopic rotational velocities, radial velocities, physical stellar parameters, and variability of the target stars. Here, we describe the target selection for this survey, as well as results from the first year of scientific observations based on spectra that will be publicly available in the SDSS-III DR10 data release. As part of this paper we present radial velocities and rotational velocities of over 200 M dwarfs, with a vsini precision of ~2km/s and a measurement floor at vsini=4km/s. This survey significantly increases the number of M dwarfs studied for rotational velocities and radial velocity variability (at ~100-200m/s), and will inform and advance the target selection for planned radial velocity and photometric searches for low-mass exoplanets around M dwarfs, such as the Habitable Zone Planet Finder, CARMENES, and TESS. Multiple epochs of radial velocity observations enable us to identify short period binaries, and adaptive optics imaging of a subset of stars enables the detection of possible stellar companions at larger separations. The high-resolution APOGEE spectra, covering the entire H band, provide the opportunity to measure physical stellar parameters such as effective temperatures and metallicities for many of these stars. At the culmination of this survey, we will have obtained multi-epoch spectra and radial velocities for over 1400 stars spanning the spectral range M0-L0, providing the largest set of near-infrared M dwarf spectra at high resolution, and more than doubling the number of known spectroscopic vsini values for M dwarfs. Furthermore, by modeling telluric lines to correct for small instrumental radial velocity shifts, we hope to achieve a relative velocity precision floor of 50m/s for bright M dwarfs. With three or more epochs, this precision is adequate to detect substellar companions, including giant planets with short orbital periods, and flag them for higher-cadence followup. We present preliminary, and promising, results of this telluric modeling technique in this paper.
Machine learning allows for efficient extraction of physical properties from stellar spectra that have been obtained by large surveys. The viability of machine-learning approaches has been demonstrated for spectra covering a variety of wavelengths and spectral resolutions, but most often for main-sequence (MS) or evolved stars, where reliable synthetic spectra provide labels and data for training. Spectral models of young stellar objects (YSOs) and low-mass MS stars are less well-matched to their empirical counterparts, however, posing barriers to previous approaches to classify spectra of such stars. In this work, we generate labels for YSOs and low-mass MS stars through their photometry. We then use these labels to train a deep convolutional neural network to predict logg, Teff, and Fe/H for stars with Apache Point Observatory Galactic Evolution Experiment (APOGEE) spectra in the DR14 data set. This "APOGEE Net" has produced reliable predictions of logg for YSOs, with uncertainties of within 0.1dex and a good agreement with the structure indicated by pre-MS evolutionary tracks, and it correlates well with independently derived stellar radii. These values will be useful for studying pre-MS stellar populations to accurately diagnose membership and ages.
We present a semi-empirical spectral classification scheme for normal B-type stars using near-infrared (NIR) spectra (1.5-1.7{mu}m) from the Sloan Digital Sky Survey Apache Point Observatory Galaxy Evolution Experiment (APOGEE2)-N data release 14 (DR14) database. The main motivation for working with B-type stars is their importance in the evolution of young stellar clusters; however, we also take advantage of having a numerous sample (316 stars) of B-type star candidates in APOGEE2-N, for which we also have optical (3600-9100{AA}) counterparts from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) survey. By first obtaining an accurate spectral classification of the sources using the LAMOST DR3 spectra and the canonical spectral classification scheme, we found a linear relation between optical spectral types and the equivalent widths of the hydrogen lines of the Brackett series in the APOGEE2-N NIR spectra. This relation extends smoothly from a similar relation for O and early B stars found by Roman-Lopes+ (2018, J/ApJ/855/68). This way, we obtain a catalog of B-type sources with features in both the optical and NIR and a classification scheme refined down to one spectral subclass.
