Value Added Catalogs

In addition to the primary SDSS photometry and spectroscopy, there are a few extra catalogs created by our collaborators that are distributed through the SAS. These Value-Added Catalogs (VACs) are listed below, and include catalogs that were released in earlier data releases.

APOGEE Value-Added Catalogs

APOGEE red-clump catalog

APOGEE’s target selection algorithm includes many red-clump (RC) stars in the APOGEE sample. A new method for identifying red-clump stars from spectrophotometric data and its application to the APOGEE data was presented in Bovy et al. (2014). This technique creates a very pure sample of red-clump stars with minimal contamination from red-giant-branch, secondary-red-clump, and asymptotic-giant-branch stars. The narrowness of the RC locus in color-metallicity-luminosity space allows distances to the stars to be assigned with an accuracy of 5%-10%. The purity is estimated to be about 95%.

The DR13 catalog is selected based on the more accurate set of spectroscopic parameters from the overall DR13 APOGEE release and therefore suffers from less contamination, leading to a slight decrease in the number of RC stars in the DR13 catalog compared to the DR12 catalog. The DR13 catalog contains 19,291 stars and is available on the SAS; its contents are described in the datamodel.

The older DR11 and DR12 catalog versions are still available. For DR11 (Niveder et al. 2014), containing 10,341 objects, the catalog is available from the SAS here, with its datamodel available here. The DR12 catalogue (Bovy et al. 2014), containing 19,937 objects, is available from the SAS here, with its datamodel available here.

Accounting for Observational Biases in APOGEE

Section 4 of Bovy et al. (2014) described how to correct for observational biases due to the APOGEE target selection (for the whole (J-Ks)0 > 0.5 sample, not just the red-clump sample). Specifically, these are the biases due to the incomplete sampling of the available targets with (J-Ks)0 > 0.5 as a function of position on the sky and magnitude. Tools to correct for these biases are included in the apogee python package and extensive documentation on how to use this package is given on the package webpage. This selection-function code has been updated for DR13 (from the DR11 version described in the paper).

Section 5 of Bovy et al. (2014) discussed astrophysical biases due to the red-clump selection. Specifically, they investigated the biases in recovering the underlying age and metallicity distribution by only selecting red-clump stars. The RC selection preferentially select stars with ages between 1 and 4 Gyr and with metallicities > -0.9. Please consult section 5 of the paper above for full details. The apogee python package also has tools for working with the astrophysical biases.

BOSS and eBOSS Value-Added Catalogs

Large Scale Structure Galaxy Catalogs

The galaxy catalogs used in the DR12 large scale structure analyses (e.g., Reid et al. 2016) are available in this location on the SAS. The files in the catalogs are described in the data model page.


Bovy et al. (2011) describes a technique for QSO target selection based on an extreme deconvolution method, which models the distribution of quasars and stars in color-color space, including their errors. The associated catalog is available on the SAS. The files in the catalog are described in the data model.

Galaxy Parameters

Catalogs of galaxy properties such as stellar masses, ages, stellar formation rates, and velocity dispersions are described on the Galaxy Products page.

QSO Catalog

The French Participation Group (FPG) to SDSS-III has produced a quasar catalog for each BOSS data release, described in detail in Pâris et al. 2014 and summarized in its latest form on the DR10Q algorithms page.

QSO Variability

Variability information (Palanque-Delabrouille et al. 2016) for eBOSS quasar targets (Myers et al. 2015) using either PTF light curves or SDSS stripe 82 data. The catalogs are available on the SAS and on the CAS in tables qsoVarPTF table and the qsoVarStripe table. The files in the catalog are described in the data model page.

Photometric Redshift Distributions

Sheldon et al. (2012) have created a set of photometric redshift probability distributions for galaxies in the SDSS-III imaging data. The catalog is available on the SAS. The files in the catalog are described in the data model.

ELG Fisher selection

Two wide-field catalogs of photometrically-selected emission line galaxies (ELGs) at z ≈ 0.8 using either SDSS+WISE imaging or SDSS+WISE+SCUSS imaging. The catalogs were obtained using a Fisher discriminant technique described in Raichoor et al. (2016). The two catalogs are themselves described in Delubac et al. (in press). These catalogs are targeting candidates to be used for the ELG program of eBOSS. The catalogs are available on the SAS. The files in the catalog are described in the data model page.

Composite Spectra of Emission-line Galaxies

The higher-redshift coverage of the eBOSS ELG sample enables access to the near-ultraviolet wavelength region, which includes a collection of atomic absorption and emission lines that are informative for the baryonic processes in galaxy formation (Zhu et al. 2015). The spectroscopic data itself therefore are of great interest, and we publish the composite (continuum-normalized) spectra of emission-line galaxies from the pilot observation as this value-added catalog. The catalogs are available on the SAS. The files in the catalogs are described in the data model page.

WISE Forced Photometry

DR13 includes “forced photometry” matching between SDSS and WISE sources. The WISE forced photometry catalog is available from the WISEForcedTarget directory of the SAS, and the wiseForcedTarget table of the CAS. Columns are described in the Data Model.

The WISE forced photometry assumes that all objects detected and measured by SDSS appear in the WISE images with the same morphologies, and then asks how bright those objects should be to best match the WISE data. This is useful because it allows us to extract information from the WISE images using knowledge of the existence and shapes of objects from the higher-resolution SDSS imaging. There is no need for catalog matching, and all sources get a flux measurement, even if the flux is below a formal detection limit. (Low-significance flux measurements will still be noisy, of course!) This allows, for example, making statistical measures of the WISE flux of classes of SDSS objects (so-called, stacking analyses).

The catalog is described in detail in Lang, Hogg, & Schlegel 2014.

Redshift Measurement and Spectral Classification Catalog with Redmonster

Catalogue of DR13 luminous red galaxies (LRG) redshifts from models using single, theoretically-motivated templates and restricted to exclude non-physical solutions. These models are gridded on physical parameters; thus, the catalogue includes estimates for those physical parameters in addition to a higher success rate than the spectro1d pipeline. The redmonster software is detailed in full in Hutchinson et al. (2016). The catalog is available on the SAS, and the files in the catalog are described in the data model page.

SPIDERS Value-Added Catalogs

SPIDERS target selection catalogs

The SPIDERS Tier-0 target catalogs (Clerc et al., submitted ; Dwelly et al. in prep.), i.e. AGN and galaxy clusters candidates, were obtained by matching X-ray information from the ROSAT All-Sky Survey (RASS) and from XMM-Newton to multi-band photometric data.

The SPIDERS AGN target catalogs contain 9,028 candidate targets from RASS and 819 from XMMSL. They enclose information on the X-ray sources, including flux measurements, and a quantitative measure of the reliability of the association to optical and AllWISE data. The counterparts to X-ray extended sources (galaxy clusters) were identified using a red-sequence finding algorithm adapted from RedMapper (Rykoff et al. 2014). The target list contains galaxies likely to belong to a galaxy cluster, as indicated by their color, distance to the center and luminosity. The SPIDERS Galaxy Cluster target list contains 94,883 and 3,839 objects for RASS and XMM respectively. We additionally provide targeting catalogs for the SEQUELS area, similarly constructed although differing in their association and selection methods.

Details on target selection are on this page: SPIDERS target selection. The catalogs are available on the SAS. The files in the catalogs are described in the data model page.

The SPIDERS-Clusters demonstration sample catalogue

We provide the catalogue of X-ray detected galaxy clusters spectroscopically confirmed using SEQUELS-DR12 SPIDERS spectroscopic data (Clerc et al. submitted). Galaxy clusters were identified through the emission of their hot baryonic component as X-ray extended sources from the ROSAT All-Sky Survey (RASS). The optical counterparts were found by optimally searching photometric data for the existence of a red-sequence formed by their member galaxies. Spectroscopic redshifts obtained by SPIDERS (in the SEQUELS programme) provide definitive confirmation of the clustered nature of these objects and their redshift (up to z~0.6). We assigned cluster membership combining an algorithm and visual validation of individual objects. The gas properties derived from X-ray observations (luminosity, temperature, R200) are derived using precise cluster redshifts (Δz ~ 0.001). We compute galaxy cluster velocity dispersions using several methods adapted to the low number of spectroscopic members per system (of the order 15-40) and we show that their values correlate with cluster X-ray luminosities, within expectations.

The catalogs are available on the SAS. The files in the catalogs are described in the data model page.

SEGUE Value-Added Catalogs

This catalog provides the [α/Fe] ratios for SDSS and SEGUE stars from Lee et al. 2011. They are able to determine [α/Fe] abundance to an error less than 0.1 dex for stars with Teff between 4500 and 7500 K, log g between 1.5 and 5.0, [Fe/H] between -1.4 and +0.3, and S/N greater than 20. To accomplish this precision for a star with [Fe/H] < -1.4, a spectrum with S/N larger than 25 is required. The [α/Fe] abundance ranges from -0.1 to +0.6.

These abundance measurements were tested on degraded ELODIE spectra, samples of high- (R=15,000) and medium-resolution (R=6,000) spectra, and six open and globular clusters.

Certain aspects of the SEGUE target selection algorithm, in addition to components of the survey’s design, will create observational biases in the sample. For example, SEGUE assigns the same number of spectroscopic fibers to each plate, regardless of the stellar density of the line-of-sight. As the stellar number density changes over the SEGUE footprint, investigations using the survey data must correct for this variable sampling to represent the true underlying Milky Way stellar distributions. In addition, some target types will require corrections for the color, magnitude, and/or proper motion selection.

Schlesinger et al. 2012 investigated these biases for cool dwarf stars in the SEGUE sample. This value-added catalog explains a technique to constrain and account for the observational biases in SEGUE. It also provides a series of weights that can be used to determine a complete, unbiased SEGUE G- and K-dwarf sample.

A list of identifiers for repeat spectroscopic observations of individual photometric targets in SEGUE. These are particularly useful for testing consistency of the SSPP.

An, Johnson, et al. (2008) have created a catalog of ugriz photometry of SDSS images near globular and open clusters. It is available from the cluster photometry catalog page of the SDSS classic website.