THE TENTH DATA RELEASE OF THE SLOAN DIGITAL SKY SURVEY: FIRST SPECTROSCOPIC DATA FROM THE SDSS-III APACHE POINT OBSERVATORY GALACTIC EVOLUTION EXPERIMENT

Stellar spectra of red giants in the H band (1.5–1.8 μm) show a rich range of absorption lines from a wide variety of elements. At these wavelengths, the absorption due to dust in the plane of the Milky Way is much reduced compared to that in the optical bands. A high-resolution study of stars in the H band allows studies of all components of the Milky Way, across the disk, in the bulge, and out to the halo.

APOGEE's goal is to trace the history of star formation in, and the assembly of, the Milky Way by obtaining H-band spectra of 100,000 red giant candidate stars throughout the Galaxy. Using an infrared multi-object spectrograph with a resolution of R ≡ λ/Δλ ∼ 22,500, APOGEE can survey the halo, disk, and bulge in a much more uniform fashion than previous surveys. The APOGEE spectrograph features a 50.8 cm × 30.5 cm mosaicked volume-phase holographic grating and a six-element camera having lenses with a maximum diameter of 40 cm. APOGEE takes advantage of the fiber infrastructure on the SDSS telescope, using 300 fibers, each subtending 2'' on the sky, distributed over the full 7 deg² field of view (with the exception of plates observed at high airmass, as noted above). The spectrograph itself sits in a temperature-controlled room, and thus does not move with the telescope. The light from the fibers falls onto three HAWAII-2RG 2K × 2K infrared detectors (Garnett et al. 2004; Rieke 2007), that cover the wavelength range from 1.514 μm to 1.696 μm, with two gaps (see Section 3.2 for details). APOGEE targets are chosen with magnitude and color cuts from photometry of the Two Micron All Sky Survey (2MASS; Skrutskie et al. 2006), with a median H = 10.9 mag and with 99.6% of the stars brighter than H = 13.8 mag (on the 2MASS Vega-based system).

The high resolution of the spectra and the stability of the instrument allow accurate radial velocities with a typical uncertainty of 100 m s⁻¹, and detailed abundance determinations for approximately 15 chemical elements. In addition to being key in identifying binary star systems, the radial velocity data are being used to explore the kinematical structure of the Milky Way and its substructures (e.g., Nidever et al. 2012) and to constrain dynamical models of its disk (e.g., Bovy et al. 2012). The chemical abundance data allow studies of the chemical evolution of the Galaxy (García Pérez et al. 2013) and the history of star formation. The combination of kinematical and chemical data will allow important new constraints on the formation history of the Milky Way.

A full overview of the APOGEE survey will be presented in S. Majewski et al. (2014, in preparation). The APOGEE instrument will be detailed in J. Wilson et al. (2014, in preparation) and is summarized here in Section 3.2. The target selection process for APOGEE is described in Zasowski et al. (2013) and is presented in brief here in Section 3.3. In Section 3.4 we describe a unique cross-targeting program between SDSS-III APOGEE and asteroseismology measurements from the NASA Kepler telescope⁹⁷ (Gilliland et al. 2010). Section 3.5 describes the reduction pipeline that processes the APOGEE data and produces calibrated one-dimensional spectra of each star, including accurate radial velocities (D. Nidever et al. 2014, in preparation). Important caveats regarding APOGEE data of which potential users should be aware are described in Section 3.6. Section 3.7 describes the pipeline that measures stellar properties and elemental abundances—the APOGEE Stellar Parameters and Chemical Abundances Pipeline (ASPCAP; M. Shetrone et al. 2014, in preparation; A. García-Pérez et al. 2014, in preparation; Mészáros et al. 2013). Section 3.8 summarizes the APOGEE data products available in DR10.

The APOGEE spectrograph measures 300 spectra in a single observation: roughly 230 science targets, 35 on blank areas of sky to measure sky emission, and 35 hot, blue stars to calibrate atmospheric absorption. This multiplexing is accomplished using the same aluminum plates and fiber optic technology as have been used for the optical spectrograph surveys of SDSS. Each plate corresponds to a specific patch of sky, and is pre-drilled with holes corresponding to the sky positions of objects in that area, meaning that each area requires one or more unique plates.

The APOGEE spectrograph uses three detectors to cover the H-band range, "blue": 1.514–1.581 μm, "green": 1.585–1.644 μm, and "red": 1.647–1.696 μm. There are two gaps, each a few nm wide, in wavelength in the spectra. The spectral line spread function spans 1.6–3.2 pixels per spectral resolution element FWHM, increasing from blue to red across the detectors. Thus most of the blue detector is under-sampled. Figure 3 shows the results of a typical exposure. Each observation consists of at least one "AB" pair of exposures for a given pointing on the sky, with the detector array mechanically offset by 0.5 pixels along the dispersion direction between the two exposures. This well-controlled sub-pixel dithering allows the derivation of combined spectra with approximately twice the sampling of the individual exposures. Thus the combined spectra are properly sampled, including all wavelengths from the blue detector. The actual line spread function as a function of wavelength is provided as a Gauss–Hermite function for each APOGEE spectrum in DR10.

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A typical observation strategy is two "ABBA" sequences. Each sequence consists of four 500 s exposures to reach the target S/N for a given observation. The combination of all "AB" or "BA" pairs for a given plate during a night is called a "visit." The visit is the basic product for what are considered individual spectra for APOGEE (although the spectra from the individual exposures are also made available). While the total exposure time for a visit is 4000 s (2 × 4 × 500 s), due to the varying lengths of night and other scheduling issues, we often gathered more or less than the standard two "ABBA" sequences on a given plate in a night. APOGEE stars are observed over multiple visits (the goal is at least three visits) to achieve the planned S/N. Figure 4 shows the distribution of the number of visits for stars included in DR10; presently, most stars have three or fewer visits, but this distribution will broaden with the final data release. These visits are separated across different nights and often different seasons, allowing us to look for radial velocity variability due to binarity on a variety of timescales. The distribution of time intervals between visits is shown in Figure 5, with peaks at one and two lunations (30 and 60 days).

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Each visit is uniquely identified by the plate number and MJD of the observation. Plates are generally re-plugged between observations, so while "plate+MJD+fiber" remains a unique identifier in APOGEE spectra as it is in optical SDSS spectra, "plate+fiber" does not refer to the same object across all visits. The spectra from all visits are co-added to produce the aggregate spectrum of the star. The final co-added spectra are processed by the stellar parameters pipeline described in Section 3.7.

The aim is for a final co-added spectrum of each star with an S/N of >100 per half-resolution element.⁹⁸ Figures 6 and 7 show the distribution of S/N; not surprisingly, S/N is strongly correlated with the brightness of the star. The DR10 data include some stars that have yet to receive their full complement of visits and thus have significantly lower quality spectra. Future data releases will include additional visits for many stars, leading to an increase in total co-added S/N as well as more refined stellar parameters.

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The APOGEE plates are drilled with the same plate-drilling machines used for BOSS, and the plate numbers are sequential. This scheme means that the BOSS and APOGEE plate numbers are interleaved and that no plate number is assigned to both a BOSS and APOGEE plate.

The quality of the APOGEE commissioning data (that taken prior to 2011 August 31) is lower than the survey data, due to optical distortions and focus issues that were resolved before the official survey was started. The biggest difference lies in the "red" chip, which has significantly worse spectral resolution in the commissioning data than in the survey data. Because of this degradation, the data were not under-sampled, and spectral dithering was not done during commissioning.

Many of the targets observed in commissioning were selected in the same way as those observed during the survey (Section 3.3), though several test plates were designed with different criteria to test the selection algorithms (e.g., without a color limit or with large numbers of potential telluric calibration stars). Total exposure times for the commissioning plates were similar to those of the survey plates. Because the spectral resolution of commissioning data is worse, it cannot be analyzed using ASPCAP with the same spectral libraries with which the survey data are analyzed. As a result, DR10 does not release any stellar parameters other than radial velocities for commissioning data; subsequent releases may include stellar parameters for APOGEE commissioning derived using appropriately matched libraries and/or with only a subset of the spectral range.

APOGEE main targets are selected from 2MASS data (Skrutskie et al. 2006) using apparent magnitude limits to meet the S/N goals and a dereddened color cut of (J − K_s)₀ > 0.5 mag to select red giants in multiple components of the Galaxy: the disk, bulge, and halo. This selection results in a sample of objects that are predominantly red giant stars with 3500 < T_eff < 5200 K and log g < 3.5 (where g is in cm s⁻² and the logarithm is base 10). Fields receiving three visits have a magnitude limit of H = 12.2; the deepest plates with 24 visits go to H = 13.8.

APOGEE has also implemented a number of ancillary programs to pursue specific investigations enabled by its unique instrument. The selection of the main target sample and the ancillary programs, together with the bit flags that can be used to identify why an object was targeted for spectroscopy, are described in detail in Zasowski et al. (2013). In DR10, APOGEE stars are named based on a slightly shortened version of their 2MASS ID (e.g., "2M21504373+4215257" is stored for the formal designation "2MASS 21504373+4215257"). A few objects that don't have 2MASS IDs are designated as "AP," followed by their coordinates.

APOGEE targets were chosen in a series of fields designed to sample a wide range of Galactic environments (Figure 1): in the halo predominantly at high latitudes, in the disk, in the central part of the Milky Way (limited in declination), as well as special targeted fields overlapping the Kepler survey (Section 3.4), and a variety of open and globular clusters with well-characterized metallicity in the literature.

The effects of Galactic extinction on 2MASS photometry can be quite significant at low Galactic latitude. We correct for this using the Spitzer IRAC GLIMPSE survey (Benjamin et al. 2003; Churchwell et al. 2009) and the Wide-field Infrared Survey Explorer (WISE; Wright et al. 2010) λ = 4.5 μm data following the Rayleigh–Jeans Color Excess Method described in Majewski et al. (2011) and Zasowski et al. (2013) using the color extinction curve from Indebetouw et al. (2005). Figure 8 shows the measured and reddening-corrected JHK_s color–color and magnitude–color diagrams for the APOGEE stars included in DR10.

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In regions of high interstellar extinction, even intrinsically blue main sequence stars can be reddened enough to overlap the nominal red giant locus. Dereddening these apparent colors allows us to remove these dwarfs with high efficiency from the final targeted sample. However, G and K dwarfs cannot be distinguished from red giants on the basis of their dereddened broadband colors, with the result that a fraction of the APOGEE sample is composed of such dwarfs. In the disk they are expected to comprise less than 20% of the sample, and this appears to be validated by our analysis of the spectra. Disk dwarfs are expected to be a larger contaminant in halo fields, so in many of these, target selection was supplemented by Washington and intermediate-band DDO51 photometry (Canterna 1976; Clark & McClure 1979; Majewski et al. 2000) using the 1.3 m telescope of the U.S. Naval Observatory, Flagstaff Station. Combining this with 2MASS photometry allows us to distinguish dwarfs and giants (see Zasowski et al. 2013 for details).

Exceptions to the (J − K_s)₀ > 0.5 mag color limit that appear in DR10 include the telluric calibration stars, early-type stars targeted in well-studied open clusters, stars observed on commissioning plates that did not employ the color limit, and stars in sparsely populated halo fields where a bluer color limit of (J − K_s)₀ > 0.3 mag was employed to ensure that all fibers were utilized. Ancillary program targets may also have colors and magnitudes beyond the limits of APOGEE's normal red giant sample.

Non-radial oscillations are detected in virtually all red giants targeted by the Kepler mission (Borucki et al. 2010; Hekker et al. 2011), and the observed frequencies are sensitive diagnostics of basic stellar properties such as mass, radius, and age (for a review, see Chaplin & Miglio 2013). Abundances and surface gravities measured from high-resolution spectroscopy of these same stars are an important test of stellar evolution models, and allow observational degeneracies to be broken.

With this in mind, the "APOKASC" collaboration was formed between SDSS-III and the Kepler Asteroseismology Science Collaboration to analyze APOGEE spectra for ∼10, 000 stars in fields observed by the Kepler telescope (see Figure 1). The joint measurement of masses, radii, ages, evolutionary states, and chemical abundances for all these stars will enable significantly enhanced investigations of Galactic stellar populations and fundamental stellar physics.

DR10 presents 4204 spectra of 2308 stars of the anticipated final APOKASC sample. Asteroseismic data from the APOKASC collaboration were used to calibrate the APOGEE spectroscopic surface gravity results for all APOGEE stars presented in DR10 (Mészáros et al. 2013). A joint asteroseismic and spectroscopic value-added catalog will be released separately (M. Pinsonneault et al. 2014, in preparation).

The processing of the two-dimensional spectrograms and extraction of one-dimensional co-added spectra will be fully described in D. Nidever et al. (2014, in preparation). We provide here a brief summary to help the reader understand how individual APOGEE exposures are processed. A 500 s APOGEE exposure actually consists of a series of non-destructive readouts every 10.7 s that result in a three-dimensional data cube. The first step in processing is to extract a two-dimensional image from a combination of these measurements. After dark current subtraction, the "up-the-ramp" values for each pixel are fit to a line to derive the count rate for that pixel. Cosmic rays create characteristic jumps in the "up-the-ramp" signal that are easily recognized, removed, and flagged for future reference. The count rate in each pixel is multiplied by the exposure time to obtain a two-dimensional image. These two-dimensional images are then dark-subtracted and flat-fielded. One-dimensional spectra are extracted simultaneously for the entire set of 300 fibers based on wavelength and profile fits from flat-field calibration images. Both the flat-field response and spectral traces are very stable due to the controlled environment of the APOGEE instrument, which has been under vacuum and at a uniform temperature continuously since it was commissioned. Wavelength calibration is performed using emission lines from thorium–argon and uranium–neon hollow cathode lamps. The wavelength solution is then adjusted from the reference lamp calibration on an exposure-to-exposure basis using the location of the night sky lines.

The individual exposure spectra are then corrected for telluric absorption and sky emission using the sky spectra and telluric calibration star spectra, and combined accounting for the dither offset between each "A" and "B" exposure. This combined visit spectrum is flux-calibrated based on a model of the APOGEE instrument's response from observations of a blackbody source. The spectrum is then scaled to match the 2MASS measured apparent H-band magnitude. A preliminary radial velocity is measured after matching the visit spectrum to one from a pre-computed grid of synthetic stellar spectra, and is stored with the individual visit spectrum.

In addition to the individual visit spectra, the APOGEE software pipeline coadds the spectra from different visits to the same field, yielding a higher S/N spectrum of each object. Figure 9 shows examples of high S/N co-added flux-calibrated spectra from APOGEE for stars with a range of T_eff and with a range of [M/H]. A final and precise determination of the relative radial velocities on each visit is determined from cross-correlation of each visit spectrum with the combined spectrum; the velocities are put on an absolute scale by cross-correlating the combined spectrum with the best-matching spectrum in a pre-computed synthetic grid. The combined spectra are output on a rest-wavelength scale with logarithmically spaced pixels with approximately three pixels per spectral resolution element.

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Users should be aware of several features and potential issues with the APOGEE data. This is the first data release for APOGEE; the handling of some of these issues by the pipelines may be improved in subsequent data releases.

Many of these issues are documented in the data by the use of bitmasks that flag various conditions. For the APOGEE spectral data, there are two bitmasks that accompany the main data products Each one-dimensional extracted spectrum includes a signal, uncertainty, and mask arrays. The mask array is a bitmask, APOGEE_PIXMASK,⁹⁹ that flags data-quality conditions that affect a given pixel. A non-zero APOGEE_PIXMASK value for a pixel indicates a potential data-quality concern that affects that pixel. Each stellar-parameters analysis of each star is accompanied by a single bitmask, APOGEE_STARFLAG,¹⁰⁰ that flags conditions at the full spectrum level.

The most important data-quality features to be aware of include:

Gaps in the spectra. There are gaps in the spectra corresponding to the regions that fall between the three detectors. There are additional gaps due to bad or hot pixels on the arrays. As multiple dithered exposures are combined to make a visit spectrum, values from missing regions cannot be used to calculate the dither-combined signal in nearby pixels; as a result, these nearby pixels are set to zero and the BADPIX bit is set for these pixels in APOGEE_PIXMASK. Generally, the bad pixels affect neighboring pixels only at a very low level, and the data in the latter may be usable; in subsequent data releases, we will preserve more of the data, while continuing to identify potential bad pixels in the pixel mask.

Imperfect night-sky-line subtraction. The Earth's atmosphere has strong and variable emission in OH lines in the APOGEE bandpass. At the location of these lines, the sky flux is many times brighter than the stellar flux for all except the brightest stars. Even if the sky subtraction algorithm were perfect, the photon noise at the positions of these sky lines would dominate the signal, so there is little useful information at the corresponding wavelengths. The spectra in these regions can show significant sky line residuals. These regions are masked for the stellar parameter analysis so that they do not impact the results. The affected pixels have the SIG_SKYLINE bit set in APOGEE_PIXMASK.

Error arrays do not track correlated errors. APOGEE spectra from an individual visit are made by combining multiple individual exposures taken at different dither positions. Because the dithers are not spaced by exactly 0.5 pixels, there is some correlation between pixels that is introduced when combined spectra are produced. The error arrays for the visit spectra do not include information about these correlations. In the visit spectra, these correlations are generally small because the dither mechanism is generally quite accurate. However, when multiple visit spectra are combined to make the final combined spectra, they must be re-sampled onto a common wavelength grid, taking into account the different observer-frame velocities of each individual visit. This re-sampling introduces significant additional correlated errors between adjacent pixels that are also not tracked in the error arrays.

Error arrays do not include systematic error floors. The errors that are reported for each spectrum are derived based on propagation of Poisson and readout noise. However, based on observations of bright hot stars, we believe that other, possibly systematic, uncertainties currently limit APOGEE observations to a maximum S/N per half resolution element of ∼200. The error arrays published in DR10 currently report the estimated errors without any contribution from a systematic component. However, for the ASPCAP analysis, we impose an error floor corresponding to 0.5% of the continuum level.

Fiber crosstalk. While an effort is made not to put faint stars adjacent to bright ones on the detector to avoid excessive spillage of light from one to the other, this occasionally occurs. We flag objects (in APOGEE_STARFLAG) with a BRIGHT_NEIGHBOR flag if an adjacent star is >10 times brighter than the object, and with a VERY_BRIGHT_NEIGHBOR flag if an adjacent star is >100 times brighter; in the latter case, the individual spectra are marked as bad and are not used in combined spectra.

Persistence in the "blue" chip. There is a known "superpersistence" in 1/3 of the region of the "blue" APOGEE data array, and to a lesser extent in some regions of the "green" chip, whereby some of the charge from previous exposures persists in subsequent exposures. Thus the values read out in these locations depend on the previous exposure history for that chip. The effect of superpersistence can vary significantly, but residual signal can amount to as much as 10%–20% of the signal from previous exposures. The current pipeline does not attempt to correct for this effect; any such correction is likely to be rather complex. For the current release, pixels known to be affected by persistence are flagged in APOGEE_PIXMASK at three different levels (PERSIST_LOW, PERSIST_MEDIUM, PERSIST_HIGH). Spectra that have significant numbers of pixels (>20% of total pixels) that fall in the persistence region have comparable bits set in the APOGEE_STARFLAG bitmask to warn that the spectra for these objects may be contaminated. In a few cases, the effect of persistence is seen dramatically as an elevated number of counts in the blue chip relative to the other arrays; these are flagged as PERSIST_JUMP_POS in APOGEE_STARFLAG. We are still actively investigating the effect of persistence on APOGEE spectra and derived stellar parameters, and are working on corrections that we intend to implement for future data releases.

The ultimate goal of APOGEE is to determine the effective temperature, surface gravity, overall metallicity, and detailed chemical abundances for a large sample of stars in the Milky Way. Stellar parameters and chemical abundances are extracted from the continuum-normalized co-added APOGEE spectra by comparing with synthetic spectra calculated using state-of-the-art model photospheres (Mészáros et al. 2012) and atomic and molecular line opacities (M. Shetrone et al., in preparation).

Analysis of high-resolution spectra is traditionally done by hand. However, given the sheer size of APOGEE's spectral database, automatic analysis methods must be implemented. For that purpose, ASPCAP searches for the best fitting spectrum through χ² minimization within a pre-computed multi-dimensional grid of synthetic spectra, allowing for interpolation within the grid. The output parameters of the analysis are effective temperature (T_eff), surface gravity (log g), metallicity ([M/H]), and the relative abundances of α elements ([α/M]),¹⁰¹ carbon ([C/M]), and nitrogen ([N/M]). The micro-turbulence quoted in the DR10 results is not an independent quantity, but is instead calculated directly from the value of log g. Figure 10 shows an example ASPCAP fit to an APOGEE spectrum of a typical star. ASPCAP will be fully described in an upcoming paper (A. García Pérez et al. 2014, in preparation).

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Chemical composition parameters are defined as follows. The abundance of a given element X is defined relative to solar values in the standard way:

$$\begin{equation} [{\rm X/H}] = \log _{10}(n_{\rm X}/n_{\rm H})_{\rm star} - \log _{10}(n_{\rm X}/n_{\rm H})_\odot \,, \end{equation} \tag{ 1 }$$

where n_X and n_H are respectively the numbers of atoms of element X and hydrogen, per unit volume, in the stellar photosphere. The parameter [M/H] is defined as an overall metallicity scaling, assuming the solar abundance pattern. The deviation of the abundance of element X from that pattern is given by

$$\begin{equation} \rm [X/M] = [X/H] - [M/H] \,. \end{equation} \tag{ 2 }$$

The α elements considered in the APOGEE spectral libraries are O, Ne, Mg, Si, S, Ca, and Ti, and [α/H] is defined as an overall scaling of the abundances of those elements, where they are assumed to vary together while keeping their relative abundances fixed at solar ratios. For DR10, we allow four chemical composition parameters to vary: the overall metallicity, and the abundances of α elements, carbon, and nitrogen. Carbon, nitrogen, and oxygen contribute significantly to the opacity in APOGEE spectra of cool giants, particularly in the form of molecular lines due to OH, CO, and CN.

3.7.1. Parameter Accuracies

3.7.2. ASPCAP Outputs

In DR10, we provide calibrated values of effective temperature, surface gravity, overall metallicity, and [α/M] for giants. In addition, we provide the raw ASPCAP results (uncalibrated, and thus, to some extent, unvalidated) for all six parameters for all stars with survey-quality data. Since commissioning data have lower resolution, different spectral libraries are needed to derive stellar parameters from them, and therefore ASPCAP results are not provided for these spectra at this time. For all stars with ASPCAP results, we also provide information about the quality of the fit (χ²) and several bitmasks (APOGEE_ASPCAPFLAG and APOGEE_PARAMFLAG) that flag several conditions that may cause the results to be less reliable. Among these conditions are abnormally high χ² in the fit, best-fit parameters near the edges of the searched range, evidence in the spectrum of significant stellar rotation, and so on. Users should check the values of these bitmasks before using the ASPCAP parameters.

Figure 11 shows the distribution of stellar properties derived by ASPCAP for stars included in DR10. The ASPCAP spectral libraries are currently only calibrated in the range 3610 < T_eff < 5255 K. Thus the reliable ASPCAP T_eff reported values lie only in this range, with a peak at about 4800 K. The surface gravity distribution peaks at log g ∼ 2.5, corresponding to red clump stars, and is strongly correlated with surface temperature. The ASPCAP models are calibrated in the range −0.5 < log g < 3.6, which is reflected in the range shown. Because of the strong concentration of targeted fields to the Galactic Plane (Figure 1), the metallicity distribution peaks just below solar levels, with a tail extending from [M/H] ∼ −0.5 to below −2.3. The [α/M] abundance distribution has both α-rich and α-poor stars, which reflects the variety of populations explored by APOGEE.

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Figure 12 shows the excellent agreement of the ASPCAP log  g, T_eff, and [M/H] values with the isochrone models of Bressan et al. (2012).

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The APOGEE data as presented in DR10 are available as the individual 500 s spectra taken on a per-exposure basis (organized both by object and by plate+MJD+fiber), as combined co-added spectra on a per-object basis, and as continuum-normalized spectra used by the APOGEE pipeline (ASPCAP) when it computes stellar properties (Section 3.7). The individual raw exposure files, processed spectra, and combined summary files of stellar parameters are provided as FITS¹⁰² files (Wells et al. 1981) through the DR10 Science Archive Server (SAS). The DR10 Catalog Archive Server (CAS) provides the basic stellar parameters (including the radial velocity) from the APOGEE spectra on a per-visit (SQL table apogeeVisit) and a co-added star basis (SQL table apogeeStar). The ASPCAP results are provided in the SQL table aspcapStar; the covariances between these parameters are given in a separate table, aspcapStarCovar.

To allow one to recreate the sample selection, all of the parameters used in selecting APOGEE targets are provided in DR10 in the SQL table apogeeObject.

Example queries for APOGEE data using the CAS are provided as part of the DR10 web documentation.¹⁰³

Ross et al. (2012) describe the quasar target selection used in BOSS. DR10 includes one new quasar target class, BOSS_WISE_SUPP, which uses photometry from SDSS and WISE to select z > 2 quasars that the standard BOSS quasar target selection may have missed, and to explore the properties of quasars selected in the infrared.

These objects were required to have detections in the 3.6 μm, 4.5 μm, and 12 μm bands, and to be point sources in SDSS imaging. They were selected with the following color cuts:

$$\begin{equation} (u-g)>0.4 \ {\rm and}\ (g-r)<1.3. \end{equation} \tag{ 3 }$$

The requirement of a 12 μm detection removes essentially all stellar contamination, without any WISE color cuts.

There are 5007 spectra from this sample in DR10, with a density of ∼1.5 deg⁻² over the ∼3100 deg² of new area added by BOSS in DR10. Almost 3000 of these objects are spectroscopically confirmed to be quasars, with redshifts up to z = 3.8. Nine-hundred ninety-nine of these objects have z > 2.15.

Given the use of WISE photometry in target selection, we have imported the WISE All-Sky Release catalog (Cutri et al. 2012) into the SDSS CAS, and performed an astrometric cross-match with 4'' matching radius with the SDSS catalog objects. We find no systematic shift between the WISE and SDSS astrometric systems; 4'' extends well into the tail of the match distance distribution. The results of this matching are also available as individual files in the SAS.

We have become aware of transient hot columns on the spectrograph CCDs. Because fiber traces lie approximately along columns, a bad column can adversely affect a large swath of a given spectrum. With this in mind, unusual-looking spectra associated with fibers 40, 556, and 834 and fibers immediately adjacent should be treated with suspicion; these objects are often erroneously classified as z > 5 quasars. We will improve the masking of these bad columns in future data releases.

We have identified 2748 objects with spectra whose astrometry is unreliable in the SDSS imaging due to tracking or focus problems of the SDSS telescope while scanning. As a consequence, the fibers may be somewhat offset from the true position of the object, often missing it entirely (and thus having a spectrum with no signal). The redshift determination of each object is accompanied by a warning flag, ZWARNING, which indicates that the results are not reliable (Table 2 of Dawson et al. 2013). Objects with bad astrometry are assigned bit 8, BAD_TARGET in ZWARNING.

Estimating stellar population properties for galaxies from SDSS spectra continues to be an active field with different valid approaches. DR9 included various estimates of stellar population parameters, including:

• 1.  
  "Portsmouth" stellar masses derived from spectroscopic redshifts plus the SDSS imaging ugriz (Maraston et al. 2013);
• 2.  
  "Portsmouth" measurements of stellar kinematics and emission-line fluxes combined with model spectral fits to the full spectra (Thomas et al. 2013); and
• 3.  
  "Wisconsin" principal component analysis (PCA) of the stellar populations using fits to the wavelength range λ = 3700–5500 Å (Chen et al. 2012).

The latter two spectral fits include estimates of stellar velocity dispersions. These measurements agree with each other and the pipeline estimates of Bolton et al. (2012) within their measurement errors, but slight systematic offsets remain. For a detailed comparison we refer the reader to Thomas et al. (2013).

All stellar population calculations use the WMAP7 ΛCDM cosmology with H₀ = 70 km s⁻¹ Mpc⁻¹, Ω_M = 0.274, and Ω_Λ = 0.726 (Komatsu et al. 2011).

In DR9, these models were calculated just for BOSS spectra; in DR10 they are extended to the ∼930, 000 galaxy spectra from SDSS-I/II. The Portsmouth code results in DR10 now also include the full stellar mass probability distribution function for each spectrum. The Wisconsin PCA code in DR9 used the stellar population model of Bruzual & Charlot (2003). In DR10, we have added the stellar population synthesis model of Maraston & Strömbäck (2011). In addition, the covariance matrix in the flux density in neighboring pixels due to errors in spectrophotometry has been updated by using all of the repeat galaxy observations in DR10, rather than the 5000 randomly selected repeat galaxy observations used in DR9. This covariance is important in fitting stellar population models to the spectra.

In DR9 we also provided measurements of emission-line fluxes and equivalent widths as well as gas kinematics (Thomas et al. 2013). However, the continuum fluxes as listed in the Portsmouth DR9 catalog needed to be corrected to rest-frame by multiplication by 1 + z. Consequently, the equivalent widths needed to be divided by the same factor 1 + z to be translated into the rest frame. In DR10, the continuum fluxes and equivalent widths have these correction factors applied, and are presented in the rest-frame.

In DR10, we also include results from the Granada Stellar Mass code (A. Montero-Dorta et al. 2014, in preparation) based on the publicly available "Flexible Stellar Population Synthesis" code of Conroy et al. (2009). The Granada FSPS product follows a similar spectrophotometric SED fitting approach as that of the Portsmouth galaxy product, but using different stellar population synthesis models, with varying star formation history (based on simple τ-models), metallicity and dust attenuation. The Granada FSPS galaxy product provides spectrophotometric stellar masses, ages, specific star formation rates, and other stellar population properties, along with corresponding errors, for eight different models, which are generated by applying simple, physically motivated priors to the parent grid. These eight models are based on three binary choices: (1) including or not including dust; (2) using the Kroupa (2001) versus the Salpeter (1955) stellar initial mass function; and (3) two different configurations for the galaxy formation time: either the galaxy formed within the first 2 Gyr following the Big Bang (z ∼ 3.25), or the galaxy formed between the time of the Big Bang and two Gyr before the observed redshift of the galaxy.