The Sloan Digital Sky Survey Quasar Catalog: Twelfth data release
1 INAF–Osservatorio Astronomico di Trieste, via G. B. Tiepolo 11, 34131 Trieste, Italy
2 Aix-Marseille Université, CNRS, LAM (Laboratoire d’Astrophysique de Marseille) UMR 7326, 13388 Marseille, France
3 UPMC-CNRS, UMR 7095, Institut d’Astrophysique de Paris, 75014 Paris, France
4 Department of Physics, Drexel University, 3141 Chestnut Street, Philadelphia, PA 19104, USA
5 Institute for Astronomy, SUPA (Scottish Universities Physics Alliance), University of Edinburgh, Royal Observatory, Edinburgh, EH9 3HJ, UK
6 Department of Physics and Astronomy, University of Wyoming, Laramie, WY 82071, USA
7 Max-Planck-Institut für Astronomie, Königstuhl 17, 69117 Heidelberg, Germany
8 APC, Astroparticule et Cosmologie, Université Paris Diderot, CNRS/IN2P3, CEA/Irfu, Observatoire de Paris, Sorbonne Paris Cité, 10 rue Alice Domon & Léonie Duquet, 75205 Paris Cedex 13, France
9 Instituto de Astrofisica de Canarias (IAC), 38200 La Laguna, Tenerife, Spain
10 Universidad de La Laguna (ULL), Dept. Astrofisica, 38206 La Laguna, Tenerife, Spain
11 Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA
12 CEA, Centre de Saclay, Irfu/SPP, 91191 Gif-sur-Yvette, France
13 Department of Astronomy, University of Florida, Gainesville, FL 32611-2055, USA
14 Princeton University Observatory, Peyton Hall, Princeton, NJ 08544, USA
15 Instituto de Física Teórica (UAM/CSIC), Universidad Autónoma de Madrid, Cantoblanco, 28049 Madrid, Spain
16 Department of Astronomy and Astrophysics, University of Toronto, 50 St. George Street, Toronto, ON, M5S 3H4, Canada
17 Apache Point Observatory and New Mexico State University, PO Box 59, Sunspot, NM, 88349-0059, USA
18 Sternberg Astronomical Institute, Moscow State University, Moscow
19 Department of Astronomy & Astrophysics, The Pennsylvania State University, University Park, PA 16802, USA
20 Institute for Gravitation and the Cosmos, The Pennsylvania State University, University Park, PA 16802, USA
21 Department of Physics, 104 Davey Lab, The Pennsylvania State University, University Park, PA 16802, USA
22 Dipartimento di Fisica e Astronomia, Università di Bologna, viale Berti Pichat 6/2, 40127 Bologna, Italy
23 INAF–Osservatorio Astronomico di Bologna, via Ranzani 1, 40127 Bologna, Italy
24 Max-Planck-Institut für Extraterrestrische Physik, Giessenbachstrasse 1, 85741 Garching, Germany
25 McWilliams Center for Cosmology, Dept. of Physics, Carnegie Mellon University, Pittsburgh PA 15213, USA
26 Steward Observatory, University of Arizona, Tucson, AZ 85750, USA
27 Department of Physics and Astronomy, York University, 4700 Keele St., Toronto, ON, M3J 1P3, Canada
28 Kavli Institute for Astronomy and Astrophysics, Peking University, 100871 Beijing, PR China
29 Institute of Astronomy, University of Cambridge, Madingley Road, Cambridge CB3 0HA, UK
30 Kavli Institute for Cosmology, University of Cambridge, Madingley Road, Cambridge CB3 0HA, UK
31 Campus of International Excellence UAM+CSIC, Cantoblanco, 28049 Madrid, Spain
32 Instituto de Astrofísica de Andalucía (CSIC), Glorieta de la Astronomía, 18080 Granada, Spain
33 INFN/National Institute for Nuclear Physics, via Valerio 2, 34127 Trieste, Italy
34 Department of Astronomy and CCAPP, Ohio State University, Columbus, OH 43201, USA
Corresponding author: Isabelle Pâris, e-mail: email@example.com
Received: 18 December 2015
Accepted: 23 August 2016
We present the Data Release 12 Quasar catalog (DR12Q) from the Baryon Oscillation Spectroscopic Survey (BOSS) of the Sloan Digital Sky Survey III. This catalog includes all SDSS-III/BOSS objects that were spectroscopically targeted as quasar candidates during the full survey and that are confirmed as quasars via visual inspection of the spectra, have luminosities Mi [z = 2] < −20.5 (in a ΛCDM cosmology with H0 = 70 km s-1 Mpc-1, ΩM = 0.3, and ΩΛ = 0.7), and either display at least one emission line with a full width at half maximum (FWHM) larger than 500 km s-1 or, if not, have interesting/complex absorption features. The catalog also includes previously known quasars (mostly from SDSS-I and II) that were reobserved by BOSS. The catalog contains 297 301 quasars (272 026 are new discoveries since the beginning of SDSS-III) detected over 9376 deg2 with robust identification and redshift measured by a combination of principal component eigenspectra. The number of quasars with z > 2.15 (184 101, of which 167 742 are new discoveries) is about an order of magnitude greater than the number of z > 2.15 quasars known prior to BOSS. Redshifts and FWHMs are provided for the strongest emission lines (C iv, C iii], Mg ii). The catalog identifies 29 580 broad absorption line quasars and lists their characteristics. For each object, the catalog presents five-band (u, g, r, i, z) CCD-based photometry with typical accuracy of 0.03 mag together with some information on the optical morphology and the selection criteria. When available, the catalog also provides information on the optical variability of quasars using SDSS and Palomar Transient Factory multi-epoch photometry. The catalog also contains X-ray, ultraviolet, near-infrared, and radio emission properties of the quasars, when available, from other large-area surveys. The calibrated digital spectra, covering the wavelength region 3600–10 500 Å at a spectral resolution in the range 1300 < R < 2500, can be retrieved from the SDSS Catalog Archive Server. We also provide a supplemental list of an additional 4841 quasars that have been identified serendipitously outside of the superset defined to derive the main quasar catalog.
Key words: catalogs / surveys / quasars: general
© ESO, 2017
Since the discovery of the first quasar by Schmidt (1963), each generation of spectroscopic surveys has enlarged the number of known quasars by roughly an order of magnitude: the Bright Quasar Survey (Schmidt & Green 1983) reached the 100 discoveries milestone, followed by the Large Bright Quasar Survey (LBQS; Hewett et al. 1995) and its 1000 objects, then the ~25 000 quasars from the 2dF Quasar Redshift Survey (2QZ; Croom et al. 2004), and the Sloan Digital Sky Survey (SDSS; York et al. 2000) with over 100 000 new quasars (Schneider et al. 2010). Many other surveys have also contributed to increase the number of known quasars (e.g. Osmer & Smith 1980; Boyle et al. 1988; Storrie-Lombardi et al. 1996). Most of these objects have redshifts of z < 2. The main goal of the Baryon Oscillation Spectroscopic Survey (BOSS; Dawson et al. 2013), the main dark time survey of the third stage of the SDSS (SDSS-III; Eisenstein et al. 2011), is to detect the characteristic scale imprinted by baryon acoustic oscillations (BAO) in the early universe from the spatial distribution of both luminous red galaxies at z ~ 0.7 (Anderson et al. 2012, 2014; Alam et al. 2016) and H i absorption lines in the intergalactic medium (IGM) at z ~ 2.5 (Busca et al. 2013; Slosar et al. 2013; Delubac et al. 2015). In order to achieve this goal, the quasar survey of the BOSS was designed to discover at least 15 quasars per square degree with 2.15 ≤ z ≤ 3.5 over ~10 000 deg2 (Ross et al. 2012). The final SDSS-I/II quasar catalog of Schneider et al. (2010) contained ~19 000 quasars with z > 2.15. In this paper we report on the final quasar catalog from SDSS-III, which reaches a new milestone by containing 184 101 quasars at z ≥ 2.15, 167 742 of which are new discoveries.
This paper presents the final SDSS-III/BOSS quasar catalog, denoted DR12Q, that compiles all the spectroscopically confirmed quasars identified in the course of the SDSS-III/BOSS survey and released as part of the SDSS twelfth data release (Alam et al. 2015). The bulk of the quasars contained in DR12Q come from the main SDSS-III/BOSS quasar target selection (Ross et al. 2012). The rest of the quasars were observed by SDSS-III/BOSS ancillary programs (46 574 quasars not targeted by the SDSS-III/BOSS main quasar survey; see Dawson et al. 2013; Ahn et al. 2014; Alam et al. 2015), and the Sloan Extended Quasar, ELG and LRG Survey (SEQUELS) that is the SDSS-IV/eBOSS pilot survey (20 133 quasars not targeted by the SDSS-III/BOSS main quasar survey; Dawson et al. 2016; Myers et al. 2015). In addition, we catalog quasars that are serendipitously targeted as part of the SDSS-III/BOSS galaxy surveys. DR12Q contains 297 301 unique quasars, 184 101 having z > 2.15, over an area of 9376 deg2. Note that this catalog does not include all the previously known SDSS quasars but only the ones that were re-observed by the SDSS-III/BOSS survey. Out of 105 783 quasars listed in DR7Q (Schneider et al. 2010), 80 367 were not re-observed as part of SDSS-III/BOSS. In this paper, we describe the procedures used to compile the DR12Q catalog and changes relative to the previous SDSS-III/BOSS quasar catalogs (Pâris et al. 2012, 2014).
We summarize the target selection and observations in Sect. 2. We describe the visual inspection process and give the definition of the DR12Q parent sample in Sect. 3. General properties of the DR12Q sample are reviewed in Sect. 4 and the format of the file is described in Sect. 5. Supplementary lists are presented in Sect. 6. Finally, we conclude in Sect. 7.
In the following, we will use a ΛCDM cosmology with H0 = 70 km s-1 Mpc-1, ΩM = 0.3, ΩΛ = 0.7 (Spergel et al. 2003). We define a quasar as an object with a luminosity Mi[z = 2] < −20.5 and either displaying at least one emission line with FWHM> 500 km s-1 or, if not, having interesting/complex absorption features. Indeed, a few tens of objects have very weak emission lines but the Lyman-α forest is seen in their spectra (Diamond-Stanic et al. 2009), and thus we include them in the DR12Q catalog. About 200 quasars with unusual broad absorption lines are also included in our catalog (Hall et al. 2002) even though they do not formally meet the requirement on emission-line width. All magnitudes quoted here are Point Spread Function (PSF) magnitudes (Stoughton et al. 2002) and are corrected for Galactic extinction (Schlegel et al. 1998).
The measurement of the clustering properties of the IGM using the Lyman-α forest to constrain the BAO scale at z ~ 2.5 at the percent level requires a surface density of at least 15 quasars deg-2 in the redshift range 2.15–3.5 over about 10 000 square degrees (McDonald & Eisenstein 2007). To meet these requirements, the five-year SDSS-III/BOSS program observed about 184 000 quasars with 2.15 <z< 3.5 over 9376 deg2. The precision reached is of order 4.5% on the angular diameter distance and 2.6% in the Hubble constant at z ~ 2.5 (Eisenstein et al. 2011; Dawson et al. 2013; Alam et al. 2015). The BAO signal was detected in the auto-correlation of the Lyman-α forest (Busca et al. 2013; Slosar et al. 2013; Delubac et al. 2015) and in the cross-correlation of quasars with the Lyman-α forest (Font-Ribera et al. 2014) at z ~ 2.5 using previous data releases of SDSS-III (Ahn et al. 2012, 2014).
The SDSS-III/BOSS quasar target selection (Ross et al. 2012,and references therein) is based on the SDSS-DR8 imaging data (Aihara et al. 2011) which include the SDSS-I/II data with an extension to the South Galactic Cap (SGC). Imaging data were gathered using a dedicated 2.5 m wide-field telescope (Gunn et al. 2006) to collect light for a camera with 30 2k × 2k CCDs (Gunn et al. 1998) over five broad bands – ugriz (Fukugita et al. 1996). A total of 14 555 unique square degrees of the sky were imaged by this camera, including contiguous areas of ~7500 deg2 in the North Galactic Cap (NGC) and ~3100 deg2 in the SGC that comprise the uniform “Legacy” areas of the SDSS (Aihara et al. 2011). These data were acquired on dark photometric nights of good seeing (Hogg et al. 2001). Objects were detected and their properties were measured by the photometric pipeline (Lupton et al. 2001; Stoughton et al. 2002) and calibrated photometrically (Smith et al. 2002; Ivezić et al. 2004; Tucker et al. 2006; Padmanabhan et al. 2008), and astrometrically (Pier et al. 2003). The SDSS-III/BOSS limiting magnitudes for quasar target selection are r ≤ 21.85 or g ≤ 22.
The measurement of clustering in the IGM is independent of the properties of background quasars used to trace the IGM, allowing for a heterogeneous target selection to be adopted in order to achieve the main cosmological goals of BOSS. Conversely there is the desire to perform demographic measurements and quasar physics studies using a uniformly-selected quasar sample (e.g. White et al. 2012; Ross et al. 2013; Eftekharzadeh et al. 2015). Thus, a strategy that mixes a heterogeneous selection to maximize the surface density of z> 2.15 quasars, with a uniform subsample has been adopted by SDSS-III/BOSS (Ross et al. 2012).
On average, 40 fibers per square degree were allocated to the SDSS-III/BOSS quasar survey. About half of these fibers are selected by a single target selection in order to create a uniform (“CORE”) sample. Based on tests performed during the first year of BOSS observations, the CORE selection was performed by the XDQSO method (Bovy et al. 2011). The second half of the fibers are dedicated to a “BONUS” sample designed to maximize the z> 2.15 quasar surface density. The output of several different methods – a neural network combinator (Yèche et al. 2010), a Kernel Density Estimator (KDE; Richards et al. 2004, 2009), a likelihood method (Kirkpatrick et al. 2011), and the XDQSO method with lower likelihood than in the CORE sample – are combined to select the BONUS quasar targets. Where available, near-infrared data from UKIDSS (Lawrence et al. 2007), ultraviolet data from GALEX (Martin et al. 2005), along with deeper coadded imaging in overlapping SDSS runs (Aihara et al. 2011), were also incorporated to increase the high-redshift quasar yield (Bovy et al. 2012). In addition, all point sources that match the FIRST radio survey (July 2008 version; Becker et al. 1995) within a 1′′ radius and have (u−g) > 0.4 (to filter out z< 2.15 quasars) are included in the quasar target selection.
To take advantage of the improved throughput of the SDSS spectrographs, previously known quasars from the SDSS-DR7 (Schneider et al. 2010), the 2QZ (Croom et al. 2004), the AAT-UKIDSS-DSS (AUS), the MMT-BOSS pilot survey (Appendix C in Ross et al. 2012) and quasars observed at high spectral resolution by VLT/UVES and Keck/HIRES were re-targeted. During the first two years of BOSS observations, known quasars with z> 2.15 were systematically re-observed. We extended the re-observations to known quasars with z> 1.8 starting from Year 3 in order to better characterize metals in the Lyman-α forest.
In addition to the main survey, about 5% of the SDSS-III/BOSS fibers are allocated to ancillary programs that cover a variety of scientific goals. The programs are described in the Appendix and Tables 6 and 7 of Dawson et al. (2013) and Sect 4.2 of Ahn et al. (2014). Ancillary programs whose observation started after MJD = 56 107 (29th June 2012) are detailed in Appendix A of Alam et al. (2015). The full list of ancillary programs targeting quasars (and their associated target selection bits) that are included in the present catalog is provided in Appendix A.
A significant fraction of the remaining dark time available during the final year of SDSS-III was dedicated to a pilot survey to prepare for the extended Baryonic Oscillation Spectroscopic Survey (eBOSS; Dawson et al. 2016), the Time Domain Spectroscopic Survey (TDSS; Morganson et al. 2015) and the SPectroscopic Identification of eROSITA Sources survey (SPIDERS): the Sloan Extended QUasar, ELG and LRG Survey (SEQUELS). The SEQUELS targets are tracked with the EBOSS_TARGET0 flag in DR12Q. The EBOSS_TARGET0 flag is detailed in Appendix A.3 and Table 7 of Alam et al. (2015). We provide here a brief summary of the various target selections applied to this sample.
The main SEQUELS subsample is based upon the eBOSS quasar survey (Myers et al. 2015):
The eBOSS “CORE” sample is intended to recoversufficient quasars in the redshift range0.9 < z < 2.2 for the cosmological goals of eBOSS and additional quasars at z > 2.2 to supplement BOSS. The CORE sample homogeneously targets quasars at all redshifts z > 0.9 based on the XDQSOz method (Bovy et al. 2012) in the optical and a WISE-optical color cut. In order to be selected, it is required that point sources have a XDQSOz probability to be a z > 0.9 quasar larger than 0.2 and pass the color cut mopt−mWISE ≥ (g−i) + 3 where mopt is a weighted stacked magnitude in the g, r and i bands and mWISE is a weighted stacked magnitude in the W1 and W2 bands. Quasar candidates have g < 22 or r < 22 with a surface density of confirmed new quasars (at any redshifts) of ~70 deg-2.
PTF sample: quasars over a wide range of redshifts are selected via their photometric variability measured from the Palomar Transient Factory (PTF; Rau et al. 2009; Law et al. 2009). Quasar targets have r > 19 and g < 22.5 and provide an additional 3–4 z > 2.1 quasars per deg2.
Known quasars with low quality SDSS-III/BOSS spectra (0.75 < S/N per pixel < 3) or with bad spectra are re-observed.
uvxts == 1 objects in the KDE catalog of Richards et al. (2009) are targeted (this target class will be discontinued for eBOSS).
Finally, quasars within within 1′′ of a radio detection in the FIRST point source catalog (Becker et al. 1995) are targeted.
TDSS target point sources are selected to be variable in the g, r and i bands using the SDSS-DR9 imaging data (Ahn et al. 2012) and the multi-epoch Pan-STARRS1 (PS1) photometry (Kaiser et al. 2002, 2010). The survey does not specifically target quasars but a significant fraction of targets belong to this class (Morganson et al. 2015), and are thus included in the parent sample for the quasar catalog.
Finally, the AGN component of SPIDERS targets X-ray sources detected in the concatenation of the Bright and Faint ROSAT All Sky Survey (RASS) catalogs (Voges et al. 1999, 2000) and that have an optical counterpart detected in the DR9 imaging data (Ahn et al. 2012). Objects with 17 < r < 22 that lie within 1′ of a RASS source are targeted.
Quasars selected by the various selection algorithms are observed with the BOSS spectrographs whose resolution varies from ~1300 at 3600 Å to 2500 at 10 000 Å (Smee et al. 2013). Spectroscopic observations are obtained in a series of at least three 15-min exposures. Additional exposures are taken until the squared signal-to-noise ratio per pixel, (S/N)2, reaches the survey-quality threshold for each CCD. These thresholds are (S/N)2 ≥ 22 at i-band magnitude 21 for the red camera and (S/N)2 ≥ 10 at g-band magnitude 22 for the blue camera (Galactic extinction-corrected magnitudes). The spectroscopic reduction pipeline for the BOSS spectra is described in Bolton et al. (2012). SDSS-III uses plates covered by 1000 fibers that can be placed such that, ideally, up to 1000 spectra can be obtained simultaneously. The plates are tiled in a manner which allows them to overlap (Dawson et al. 2013). A total of 2438 plates were observed between December 2009 and June 2014; some were observed multiple times. In total, 297 301 unique quasars have been spectroscopically confirmed based on our visual inspection described below. Figure 1 shows the observed sky regions. The total area covered by the SDSS-III/BOSS is 9376 deg2. Figure 2 shows the number of spectroscopically confirmed quasars with respect to their observation date.
Distribution on the sky of the SDSS-DR12/BOSS spectroscopy in J2000 equatorial coordinates (expressed in decimal degrees).
|Open with DEXTER|
Cumulative number of quasars as a function of observation date during the whole SDSS-III/BOSS survey. A total of 297 301 quasars was spectroscopically confirmed. The “flat portions” in this figure correspond to summer shutdowns.
|Open with DEXTER|
Spectra of all the SDSS-III/BOSS quasar candidates, all the SDSS-III quasar targets from ancillary programs and all the objects classified robustly as z ≥ 2 quasars by the SDSS pipeline (Bolton et al. 2012) among the galaxy targets (Reid et al. 2016) have been visually inspected. The SDSS-DR12 quasar catalog is built upon the output of the visual inspection of 546 856 such quasar candidates.
The spectra of quasar candidates are reduced by the SDSS pipeline1, which provides a classification (QSO, STAR or GALAXY) and a redshift. To achieve this, a library of stellar templates, and a principal component analysis (PCA) decomposition of galaxy and quasar spectra are fitted to each spectrum. Each class of templates is fitted in a given range of redshift: galaxies from z = −0.01 to 1.00, quasars from z = 0.0033 to 7.00, and stars from z = −0.004 to 0.004 (±1200 km s-1).
The pipeline thus provides the overall best fit (in terms of the lowest reduced χ2) and a redshift for each template and thus a classification for the object. A quality flag (ZWARNING) is associated with each measured redshift. ZWARNING = 0 indicates that the pipeline has high confidence in its estimate. This output is used as the starting point for the visual inspection process (see Bolton et al. 2012,for details).
Based on the initial SDSS pipeline classification and redshift, the quasar candidates are split into four categories: low-z (z< 2) and high-z (z ≥ 2) quasars, stars and “others”. The spectra are visually inspected through a dedicated webpage on which all spectra are matched to targeting information, imaging data and SDSS-I/II spectroscopy. The inspection is performed plate by plate for each category described above with a list of spectra whose identification and redshift can be validated at once. If an object requires a more thorough inspection, it can be inspected on a single page on which it is possible to change the redshift and identification of the object. Whenever a change of identification and/or redshift is necessary, it is done by eye. Additional flags are also set during the visual inspection when a Damped Lyman-α system or broad absorption lines (see Sect. 4.6 for further details) are seen. Finally, quality flags are set if there is an obvious reduction problem. When the redshift and identification are unambiguous based on this inspection, each object is classified QSO, Star or Galaxy and a redshift is adopted. If the pipeline redshift does not need to be modified, the SDSS pipeline redshift (Z_PIPE) and the visual inspection redshift (Z_VI) are identical. If not, the redshift is set by eye with an accuracy that cannot be better than Δz ~ 0.003. In some cases, objects undoubtedly are quasars but their redshift is uncertain; these objects are classified as QSO_Z? or QSO_BAL_Z? when the spectrum exhibits strong broad absorption lines. When the object identification is unsure they are classified either as QSO_? or as Star_?. For spectra with a moderate S/N but with a highly uncertain identification, the object is classified as ?. Finally, when the S/N is too low or the spectrum is affected by poor sky subtraction or has portions missing needed that prevent an identification, it is classified as Bad. The distinction between Bad and ? becomes somewhat subjective as the S/N decreases. Examples of spectra to illustrate these categories are shown in Fig. 3.
Examples of spectra identified as QSO_? (top left), QSO_Z? (middle left), QSO_BAL_Z? (bottom left), Star_? (top right), ? (middle right), and Bad (bottom right). The fluxes are shown in black and associated errors in green. All the spectra are smoothed over 10 pixels.
|Open with DEXTER|
Most of the quasars are observed as part of the main SDSS-III/BOSS quasar survey whose target selection is described in Ross et al. (2012) or ancillary programs targeting quasars. In addition, we also included serendipitous quasars that were found among galaxy targets. Because these latter spectra have usually low S/N, their exact identification is more difficult. Thus, specifically for these objects we adopted a binary visual inspection classification: either an object is a QSO or is not_a_QSO.
We selected objects for visual inspection from among the following targets:
quasar targets from the main SDSS-III/BOSS quasar survey:these targets can be identified with the BOSS_TARGET1 targetselection flag (see Rosset al. 2012, for more details);
ancillary programs that target quasars: these can be identified with the ANCILLARY_TARGET1 and ANCILLARY_TARGET2 target selection flags that are fully described in Appendix B of Dawson et al. (2013) and Appendix A of Alam et al. (2015);
quasar targets from the SDSS-IV pilot survey that can be identified with the EBOSS_TARGET0 flag. The meaning of each value of this target selection bit is fully described in Appendix A of Alam et al. (2015);
SDSS-III/BOSS galaxy targets that are identified by the pipeline as either QSO with z > 2 and ZWARNING set to 0, or GALAXY with the subclass BROADLINE.
These criteria led to a superset containing 546 856 objects among which we identified 297 301 QSO, 1623 QSO_?, 1490 QSO_Z?, 22 804 Galaxy, 205 282 Star, 2640 Star_?, 6292 Bad, and 2386 ?. Among the galaxy targets, 6844 objects were identified as not a QSO after their visual inspection. Finally, a total of 192 quasar targets could not be visually inspected due to bad photometric information. The identification or redshift of 53 413 objects (out of 546 856) changed with respect to the SDSS pipeline (Bolton et al. 2012). A total of 83% of objects classified by the SDSS pipeline have ZWARNING = 0, i.e. their identification and redshift are considered secure. Among this subset, the identification or redshift of 3.3% of the objects changed after visual inspection. In such a case, the redshift is adjusted by eye. For the remaining 96.7%, we kept the SDSS pipeline redshift (and associated error) and identification. Emission-line confusions are the main source of catastrophic redshift failures, and wrong identifications mostly affect stars that are confused with z ~ 1 quasars because of poor sky subtraction at the red end of their spectra. The remaining 17% of the overall sample have ZWARNING> 0, i.e. the pipeline output may not be reliable. For these objects, 41.1% of the identification or redshift changed after inspection, following the same procedure as previously. The result of the visual inspection is summarized in Table 1. The SDSS-DR12 quasar catalog lists all the firmly confirmed quasars, i.e. those identified as QSO and QSO_BAL.
Number of objects identified as such by the pipeline with any ZWARNING value (second column) and with ZWARNING = 0 (third column), and after the visual inspection (fourth column).
Together with the quasar catalog, the full result of the visual inspection, i.e. the identification of all visually inspected objects, is made available as part of the superset file from which we derive this catalog. The identification of each object described in Sect. 3.1 (e.g. QSO, QSO_Z?, Bad) is encoded with two parameters in the superset file: CLASS_PERSON and Z_CONF_PERSON. The former refers to the classification itself, QSO, Star or Galaxy, while the latter refers to our level of confidence for the redshift we associate to each object. The relation between these two parameters and the identification from Sect. 3.1 is given in Table 2. We refer the reader to Appendix B for the detailed format of the DR12 superset file, which is provided in FITS format (Wells et al. 1981).
Left panel: redshift distribution of the SDSS-DR12 (thick black histogram), SDSS-DR10 (orange histogram) and SDSS-DR7 (blue histogram) quasars over the redshift range 0–6. Right panel: redshift distribution of the SDSS-DR12 quasars for the CORE sample (dark blue histogram), BONUS sample (light blue histogram), ancillary programs (red histogram) and SEQUELS (orange histogram). The bin size of all the histograms is Δz = 0.05. The two peaks at z ~ 0.8 and z ~ 1.6 seen in the redshift distribution of the SDSS-DR10 and SDSS-DR12 quasar samples (left panel) and in the distribution of the CORE and BONUS samples (right panel) are due to known degeneracies in the quasar target selection (see Ross et al. 2012,for details).
|Open with DEXTER|
The DR12Q catalog contains a total of 297 301 unique quasars, among which 184 101 have z> 2.15. This represents an increase of 78% compared to the full SDSS-DR10 quasar catalog (Pâris et al. 2014), and 121 923 quasars are new discoveries compared to the previous release. The full SDSS-III spectroscopic survey covers a total footprint of 9376 deg2, leading to an average surface density of z> 2.15 quasars of 19.64 deg-2. A total of 222 329 quasars, 167 007 having z> 2.15, are located in the SDSS-III/BOSS main quasar survey and are targeted as described in Ross et al. (2012)2. Additional BOSS-related programs3 targeted 54 639 quasars, and SEQUELS4 targeted a total of 20 333 confirmed quasars.
SDSS-DR12 quasars have redshifts between z = 0.041 and z = 6.440. The highest redshift quasar in our sample was discovered by Fan et al. (2001)5. The redshift distribution of the entire sample is shown in Fig. 4 (left panel; black histogram) and compared to the SDSS-DR7 (Schneider et al. 2010,blue histogram) and the SDSS-DR10 (Pâris et al. 2014,orange histogram) quasar catalogs. The two peaks at z ~ 0.8 and z ~ 1.6 seen in the SDSS-DR10 and SDSS-DR12 redshift distributions are due to known degeneracies in the SDSS color space. The right panel of Fig. 4 presents the redshift distribution for each main subsample: the CORE sample (dark blue histogram) designed for quasar demographics and physics studies, the BONUS sample (light blue histogram) whose goal is to maximize the number of 2.15 ≤ z ≤ 3.5 quasars, quasars observed as part of ancillary programs (red histogram) and the SDSS-IV pilot survey, i.e. the SEQUELS sample (orange histogram).
Left panel: distribution of r PSF magnitude (corrected for Galactic extinction) for the BOSS main sample (selected by the algorithms described in Ross et al. 2012,thick black histogram), ancillary programs (red histogram) and SEQUELS (orange histogram). The bin size is Δr = 0.02. Right panel: absolute magnitude-redshift plane for SDSS-DR12 CORE+BONUS quasars (black contours), quasars observed as part of SDSS-DR12 ancillary programs (red points), SEQUELS quasars (orange points) and SDSS-DR7 quasars (blue contours). The absolute magnitudes assume H0 = 70 km s-1 Mpc-1 and the K-correction is given by Richards et al. (2006), who define K(z = 2) = 0. Contours are drawn at constant point density.
|Open with DEXTER|
The main SDSS-III/BOSS quasar survey is designed to target quasars in the redshift range 2.15 ≤ z ≤ 3.5 down to g = 22 or r = 21.85. The r-band magnitude (corrected for Galactic extinction) distribution of those quasars is displayed in Fig. 5 (left panel, black histogram). Each ancillary program has its own target selection (see e.g., Alam et al. 2015), leading to an extremely heterogeneous sample whose r-band PSF magnitude distribution is also shown in Fig. 5 (left panel, red histogram). Lastly, the SDSS-IV pilot survey (SEQUELS) focuses on quasars with 0.9 ≤ z ≤ 3.5 down to g = 22 or r = 22 (Myers et al. 2015). The r-band PSF magnitude distribution of the resulting sample is displayed in Fig. 5 (left panel, orange histogram). The right panel of Fig. 5 presents the luminosity-redshift plane for the three subsamples contributing to the present catalog: the SDSS-III/BOSS main survey (black contours), quasars observed as part of ancillary programs (red points) and SEQUELS quasars (orange points). The SDSS-DR7 quasars are plotted for reference in the same plane (blue contours). Typical quasar spectra are shown in Fig. 6.
Spectrum of the highest redshift (z = 6.440) quasar observed by BOSS is displayed in the top left panel. This quasar was discovered by Fan et al. (2001). Typical spectra of SEQUELS quasars are presented at five different redshifts: z ~ 1.2 (top right panel) and z ~ 1.6 (middle left panel). Typical BOSS quasars are shown at three different redshifts: z ~ 2.2 (middle right panel), z ~ 2.7 (bottom left panel) and z ~ 3.5 (bottom right panel). All the spectra are smoothed over 5 pixels.
|Open with DEXTER|
As explained in Sect. 2.2, a significant fraction of known quasars from DR7Q have been re-observed by the SDSS-III/BOSS survey. The main quasar target selection (Ross et al. 2012) systematically re-targeted DR7Q quasars with zDR7 ≥ 2.15 over the entire survey. Starting from Year 3, DR7Q quasars with 1.8 ≤ zDR7< 2.15 were also re-observed with the BOSS spectrograph. Other DR7Q quasars, mostly at lower redshifts, were targeted as part of SDSS-III ancillary programs. SDSS-III/BOSS spectra were obtained for 25 416 objects listed in DR7Q. A total of 25 275 quasars known from DR7Q are included in the present catalog, i.e. are classified as QSO or QSO_BAL. A total of 59 are not part of the DR12Q catalog due to a lower confidence level of their redshift estimate, i.e., they were classified as QSO_Z? or QSO_BAL_Z?, and their current identification is included in the DR12 superset file. A total of 14 quasars dropped out of the DR12Q catalog due to bad photometric information and were not visually inspected, and 67 quasars have bad spectra, mostly “empty spectra”, in SDSS-III/BOSS. Our visual inspection is based on SDSS-III/BOSS spectroscopy only and thus, those spectra were re-classified as Bad. Finally, one object, SDSS J015957.64+003310.5, had its identification changed and was reported to be a “changing-look quasar” (LaMassa et al. 2015; Merloni et al. 2015).
The DR7Q catalog contains 19 132 quasars with z ≥ 2.15. In principle, all of these objects should have been re-observed by SDSS-III/BOSS. However, 2265 DR7Q quasars lie outside of the SDSS-III/BOSS footprint and hence were not re-targeted. The other 16 867 quasars have a SDSS-III/BOSS spectrum. Since the systematic re-observation of DR7Q quasars with 1.8 ≤ z < 2.15 started in Year 3, the completeness for those objects is much lower, with a total of 5676 having a SDSS-III/BOSS spectrum (out of 15 432 DR7Q quasars in the same redshift range).
The previous SDSS quasar catalog (DR10Q; Pâris et al. 2014) contained 166 583 quasars, 166 520 are included in the DR12Q catalog. Among the 63 “missing” quasars, 60 were identified in the galaxy targets and are now part of the supplementary list (see Sect. 6). As explained in Sect. 3.2, we define our parent sample based on quasar candidates from either the main SDSS-III/BOSS survey or ancillary programs, and we also search for serendipitous quasars among galaxy targets based on the SDSS pipeline identification. The latter definition depends on the SDSS pipeline version, leading to slight variations between parent samples drawn for each data release. However, we keep track of firm identifications from previous pipeline versions and provide them in the supplementary list.
The identification of two objects reported as quasars in DR10Q changed: one is now classified as QSO_? and the second one as Bad. Those two objects are part of the DR12Q superset with their new identification. Finally, one actual quasar (SDSS J013918.06+224128.7) dropped out of the main catalog but is part of the supplementary list. This quasar was re-observed as an emission line galaxy (ELG) candidate. The target selection bits for the two spectra are inconsistent. The best spectrum as identified by the SDSS pipeline, i.e. having SPECPRIMARY = 1, is associated with the ELG target, but not with the quasar target. It is therefore not selected to be part of our parent sample.
As in DR9Q and DR10Q, we provide a uniform flag (row #31 of Table C.1) in order to identify a homogeneously selected sample of quasars. The CORE sample has been designed to have a well understood and reproducible selection function. However, its definition varied over the first year of the survey. Regions of the sky within which all the algorithms used in the quasar target selection are uniform are called “Chunks”; their definition is given in Ross et al. (2012). After Chunk 12, CORE targets were selected with the XDQSO technique only (Bovy et al. 2011). These objects have uniform = 1. Quasars in the DR12Q catalog with uniform = 2 are objects that would have been selected by XDQSO if it had been the CORE algorithm prior to Chunk 12. Objects with uniform = 2 are reasonably complete to what XDQSO would have selected, even prior to Chunk 12. DR12Q only contains information about spectroscopically confirmed quasars and not about all targets. Hence, care must be taken to draw a statistical sample from the uniform flag. See, e.g., the discussion regarding the creation of a statistical sample for clustering measurements in White et al. (2012) and Eftekharzadeh et al. (2015). Quasars with uniform = 0 are not homogeneously selected CORE targets.
The present catalog contains six different redshift estimates: the visual inspection redshift (Z_VI), the SDSS pipeline redshift (Z_PIPE), a refined PCA redshift (Z_PCA) and three emission-line based redshifts (Z_CIV, Z_CIII and Z_MGII).
As described in Sect. 3.1, quasar redshifts provided by the SDSS pipeline (Bolton et al. 2012) are the result of a linear combination of four eigenspectra. The latter were derived from a principal component analysis (PCA) of a sample of quasars with robust redshifts. Hence, this does not guarantee this value to be the most accurate (e.g. Hewett & Wild 2010; Shen et al. 2016). The SDSS pipeline has a very high success rate in terms of identification and redshift estimate, and in order to correct for the remaining misidentifications and catastrophic redshift failures, we perform the systematic visual inspection of all quasar targets. In case we modified the SDSS pipeline redshift, the visual inspection redshift provides a robust value, set to be at the location of the maximum of the Mg ii emission line, when this emission line is available in the spectrum. The estimated accuracy is Δz = 0.003. This value corresponds to the limit below which we are no longer able to see any difference by eye.
We also provide a homogeneous automated redshift estimate (Z_PCA) that is based on the result of a PCA performed on a sample of quasars with redshifts measured at the location of the maximum of the Mg ii emission line (see Pâris et al. 2012,for details). The Mg ii line is chosen as the reference because this is the broad emission line the least affected by systematic shifts with respect to the systemic redshift (e.g. Hewett & Wild 2010; Shen et al. 2016). In addition to this PCA redshift, we also provide the redshift corresponding to the position of the maximum of the three broad emission lines we fit as part of this catalog: C ivλ1550, C iii]λ1909 and Mg iiλ2800.
Hewett & Wild (2010) carefully studied the systematic emission-lines shifts in the DR6 quasar sample and computed accurate quasar redshifts by correcting for these shifts. In DR12Q, there are 5328 non-BAL quasars that have redshifts measured by Hewett & Wild (2010) available and for which we also have Mg ii redshifts that are expected to be the closest estimates to the quasar systemic redshift. Mg ii-based redshifts are redshifted by 3.3 km s-1 compared to the Hewett & Wild (2010) measurements, with a dispersion of 326 km s-1. This confirms that Mg ii redshifts provide a reliable and accurate measurement.
80 791 have the six redshift measurements provided in our catalog available. We compute the redshift difference, expressed as velocities, for Z_VI, Z_MGII, Z_PIPE, Z_CIV and Z_CIII with respect to Z_PCA. We take the latter as our reference because this measurement is uniformally run over the entire DR12Q sample. The distributions of redshift differences are shown in Fig. 7. Mg ii-based redshifts are redshifted by 2.1 km s-1 compared to the PCA redshifts with a dispersion of 680 km s-1. In average, visual inspection redshifts are blueshifted by 15.3 km s-1 with respect to the PCA redshifts with a dispersion of 529 km s-1. The SDSS pipeline estimates are redshifted by 42.7 km s-1 with a dispersion of 637 km s-1. Finally, as expected, C iv and C iii] redshifts are the most shifted with respect to the PCA redshifts with an average blueshift of 321 km s-1 and 312 km s-1 respectively.
Distribution of velocity differences between the visual inspection redshift (Z_VI, black histogram), Mg ii-based redshift (Z_MGII, red histogram), SDSS pipeline redshift (Bolton et al. 2012,blue histogram), C iv-based redshift (Z_CIV, green histogram), C iii]-based redshift (Z_CIII, cyan histogram) and the PCA redshift (Z_PCA). The bin size of all the histograms is Δv = 50 km s-1.
|Open with DEXTER|
As described in Pâris et al. (2012), quasars displaying broad absorption lines (BAL) are flagged in the course of the visual inspection of all the quasar targets. This flag (BAL_FLAG_VI, Col. #56 of Table C.1) provides qualitative information about the existence of such features only. We refer the reader to Sect. 5 of Pâris et al. (2012) for a full discussion of the robustness of the visual inspection detection of BALs. A total of 29 580 quasars have been flagged in the course of visual inspection.
In order to have a more systematic detection of BALs and quantitative measurement of their properties, we automatically search for BAL features and report metrics of common use in the community: the BALnicity index (BI; Weymann et al. 1991) and the absorption index (AI; Hall et al. 2002) of the C iv absorption troughs. We restrict the automatic search to quasars with Z_VI≥ 1.57 in order to have the full spectral coverage of C iv absorption troughs.
The BALnicity index (Col. #57) is computed bluewards of the C iv emission line and is defined as: (1)where is the normalized flux density as a function of velocity displacement from the emission-line center. The quasar continuum is estimated using a linear combination of four principal components as described in Pâris et al. (2012). is initially set to 0 and can take only two values, 1 or 0. It is set to 1 whenever the quantity is continuously positive over an interval of at least 2000 km s-1. It is reset to 0 whenever this quantity becomes negative. C iv absorption troughs wider than 2000 km s-1 are detected in the spectra of 16 442 quasars. The number of lines of sight in which BI_CIV is positive is lower than the number of visually flagged BAL for several reasons: (i) the visual inspection provides a qualitative flag for absorption troughs that do not necessarily meet the requirements defined in Eq. (1); (ii) the visual inspection is not restricted to any search window; and (iii) the visual inspection flags rely on absorption troughs due to other species in addition to C iv (especially Mg ii). The distribution of BI for C iv troughs from DR12Q is plotted in the right panel of Fig. 8 (black histogram) and is compared to previous works by Gibson et al. (2009, blue histogram) performed on DR5Q (Schneider et al. 2007) and by Allen et al. (2011, red histogram) who searched for BAL quasars in quasar spectra released as part of SDSS-DR6 (Adelman-McCarthy et al. 2008). The three distributions are normalized.
Left panel: distribution of AI for the SDSS-DR3 (magenta histogram; Trump et al. 2006) and the SDSS-DR12 (black histogram) quasars. Both distributions are normalized to have a surface area equal to 1 for log AI > 2.5. Right panel: distribution of BI from the DR12Q catalog (black histogram), from the SDSS-DR6 (red histogram; Allen et al. 2011) and from the SDSS-DR5 (blue histogram; Gibson et al. 2009). All the distributions are normalized to have their sum equal to 1.
|Open with DEXTER|
The overall shapes of the three distributions are similar. The BI distribution from Gibson et al. (2009) exhibits an excess of low-BI values compared to Allen et al. (2011) and this work. The most likely explanation is the difference in the quasar emission modeling. Allen et al. (2011) used a non-negative matrix factorization (NMF) to estimate the unabsorbed flux, which produces a quasar emission line shape akin to the one we obtain with PCA. Gibson et al. (2009) modeled the quasar continuum with a reddened power-law and strong emission lines with Voigt profiles. Power-law like continua tend to underestimate the actual quasar emission and hence, the resulting BI values tend to be lower than the one computed when the quasar emission is modeled with NMF or PCA methods.
For weaker absorption troughs, we compute the absorption index (Col. #59) as defined by Hall et al. (2002): (2)where is the normalized continuum and has the same definition as in Eq. (1)except that the threshold to set C to 1 is reduced to 450 km s-1. Following Trump et al. (2006), we calculate the reduced χ2 for each trough, i.e. where C = 1: (3)where N is the number of pixels in the trough, is the normalized flux and σ the estimated rms noise for each pixel. The greater the value of , the more likely the trough is not due to noise. Following the recommendations of Trump et al. (2006), we report AIs when at least one C iv absorption trough is detected with . A total of 48 863 quasars satisfy this definition. The distribution of AI with is shown in the left panel of Fig. 8 (black histogram) and is compared to the results of Trump et al. (2006, magenta histogram). Both distributions are normalized to have a surface area equal to 1 for log AI > 2.5. The distributions are similar. The main difference between the two distributions is the existence of a tail at low AI in DR12Q. This is due to the modified definition for AI used in Trump et al. (2006): the 0.9 factor in Eq. (2)was removed and the detection threshold was larger (1000 km s-1 instead of 450 km s-1 here).
We also report the number of troughs detected with widths larger than 2000 km s-1 (Col. #62 in Table C.1) and larger than 450 km s-1 (Col. #65) together with the velocity ranges over which these troughs are detected (Cols. #63-64 and #66-67, respectively).
Format of the binary FITS file that contains “trough-by-trough” information for BAL quasars.
BAL information reported in the DR12Q catalog is computed over all the absorption troughs that are detected. However, out of 29 580 quasars with BAL_FLAG_VI = 1, i.e. flagged during the visual inspection process, 16 693 have more than one absorption trough larger than 450 km s-1 detected in the spectrum (out of 21 444 with AI > 0), and 2564 with more than one absorption trough larger than 2000 km s-1 (out of 15 044 with BI > 0). We provide detailed “trough-by-trough” information for all tes (Bal quasar spectcpan>.gt pr (bla27999-SHullspan> 0). We dspectcpahan 20be at the lo /aa2">Hewett aasse bro2EXTER">Ope cles/aan,bin17/01/aa275:/articles/a="/articles/aa/full_html/2017/01/aa27999-15/aa27999-15.html#F5">5 (left panel, black histog10.png"> has the rely ed taflu017/019-15.html#T7">C.1) and larger than 450 the ull_html/2017/01/aa27999-15/at5-eq12formed o with uniform = 0 are not homogeneou9r>
044 mo un-w fllengsim fochf 29 SDSSdiv>orrectingopositive n. How>The prFIRSTs/adios contribsar spectra released as part of SDSS-DR6 (Hewett & Wild 2010; : distribu96on of AI for the SDSS-DR3 (magenta histogram; Hewett & Wild 2010; /full_h199cles/aa/aa27999-15/aa27999-15.html#R33">Hewett & Wild 2010; .
80 7:he resulting foryt01/aa2799 course /a>,aclpoe. Ties in etg