This is the result of the query::
select
objID, field.run, field.rerun, field.camcol, field.fieldId,
obj, ra, dec, raErr, decErr, raDecCorr,
offsetRa_u, offsetRa_g, offsetRa_r, offsetRa_i, offsetRa_z,
offsetDec_u, offsetDec_g, offsetDec_r, offsetDec_i, offsetDec_z,
u, g, r, i, z, err_u, err_g, err_r, err_i, err_z,
mjd_u, mjd_g, mjd_r, mjd_i, mjd_z
from
PhotoObjAll
join
field
on (field.fieldId=PhotoObjAll.fieldId)
on SDSS DR7, kindly provided by the Potsdam mirror. All angular
quantities are given in degrees here.
From the Sloan Digital Sky Survey (SDSS) Data Release 12, which covers the full Baryonic Oscillation Spectroscopic Survey (BOSS) footprint, we investigate the possible variation of the fine-structure constant over cosmological time-scales. We analyse the largest quasar sample considered so far in the literature, which contains 13175 spectra (10363 from SDSS-III/BOSS DR12+2812 from SDSS-II DR7) with redshift z<1. We apply the emission-line method on the [OIII] doublet ({lambda}{lambda}4960, 5008{AA}) and obtain {Delta}{alpha}/{alpha}=(0.9+/-1.8)x10^-5^ for the relative variation of the fine-structure constant. We also investigate the possible sources of systematics: misidentification of the lines, sky OH lines, H{beta} and broad line contamination, Gaussian and Voigt fitting profiles, optimal wavelength range for the Gaussian fits, chosen polynomial order for the continuum spectrum, signal-to-noise ratio and good quality of the fits. The uncertainty of the measurement is dominated by the sky subtraction. The results presented in this work, being systematics limited, have sufficient statistics to constrain robustly the variation of the fine-structure constant in redshift bins ({Delta}z~0.06) over the last 7.9Gyr. In addition, we study the [NeIII] doublet ({lambda}{lambda}3869, 3968{AA}) present in 462 quasar spectra and discuss the systematic effects on using these emission lines to constrain the fine-structure constant variation. Better constraints on {Delta}{alpha}/{alpha}(<10^-6^) using the emission-line method would be possible with high-resolution spectroscopy and large galaxy/qso surveys.
The observed relation between the soft X-ray and the optical-ultraviolet emission in active galactic nuclei (AGNs) is nonlinear and it is usually parametrized as a dependence between the logarithm of the monochromatic luminosity at 2500{AA} and at 2keV. Previous investigations have found that the dispersion of this relation is rather high (~0.35-0.4 in log units), which may be caused by measurement uncertainties, variability, and intrinsic dispersion due to differences in the AGN physical properties (e.g., different accretion modes). We show that, once optically selected quasars with homogeneous SED and X-ray detection are selected, and dust reddened and/or gas obscured objects are not included, the measured dispersion drops to significantly lower values (i.e., ~0.21-0.24dex). We show that the residual dispersion is due to some extent to variability, and to remaining measurement uncertainties. Therefore, the real physical intrinsic dispersion should be <0.21dex. Such a tight relation, valid over four decades in luminosity, must be the manifestation of an intrinsic (and universal) physical relation between the disk, emitting the primary radiation, and the hot electron corona emitting X-rays.
The fourth edition of the Sloan Digital Sky Survey (SDSS) Quasar Catalog, made from the SDSS Fifth Data Release, contains 77,429 objects; this is an increase of over 30,000 entries since the previous edition (Schneider et al., Cat. <VII/243>). The catalog consists of the objects in the SDSS Fifth Data Release that have luminosities larger than M_i_=-22.0 (in a cosmology with Ho=70km.s-1.Mpc-1, {Omega}_M_=0.3, and {Omega}_{Lambda}_=0.7), have at least one emission line with FWHM larger than 1000km.s-1 or have interesting or complex absorption features, are fainter than i~15.0, and have highly reliable redshifts. The area covered by the catalog is about 5740deg^2^. The quasar redshifts range from 0.08 to 5.41, with a median value of 1.48; the catalog includes 891 quasars at redshifts greater than 4, of which 36 are at redshifts greater than 5. Approximately half of the catalog quasars have i<19; nearly all have i<21. For each object the catalog presents positions accurate to better than 0.2" rms per coordinate, five-band (ugriz) CCD-based photometry with typical accuracy of 0.03mag, and information on the morphology and selection method. The catalog also contains basic radio, near-infrared, and X-ray emission properties of the quasars, when available, from other large-area surveys. The calibrated digital spectra cover the wavelength region 3800-9200{AA} at a spectral resolution of about 2000; the spectra can be retrieved from the public database using the information provided in the catalog. The average SDSS colors of quasars as a function of redshift, derived from the catalog entries, are presented in tabular form. Approximately 96% of the objects in the catalog were discovered by the SDSS.
The current view of galaxy formation holds that all massive galaxies harbor a massive black hole at their center, but that these black holes are not always in an actively accreting phase. X-ray emission is often used to identify accreting sources, but for galaxies that are not harboring quasars (low-luminosity active galaxies), the X-ray flux may be weak, or obscured by dust. To aid in the understanding of weakly accreting black holes in the local universe, a large sample of galaxies with X-ray detections is needed. We cross-match the ROSAT All Sky Survey (RASS) with galaxies from the Sloan Digital Sky Survey Data Release 4 (SDSS DR4) to create such a sample. Because of the high SDSS source density and large RASS positional errors, the cross-matched catalog is highly contaminated by random associations. We investigate the overlap of these surveys and provide a statistical test of the validity of RASS-SDSS galaxy cross-matches.
We compile black hole (BH) masses for ~60000 quasars in the redshift range 0.1~<z~<4.5 included in the Fifth Data Release of the Sloan Digital Sky Survey (Schneider et al. 2007, Cat. VII/252), using virial BH mass estimators based on the H{beta}, MgII, and CIV emission lines.
The study of the interesting cosmological properties of voids in the Universe depends on the efficient and robust identification of such voids in galaxy redshift surveys. Recently, Sutter et al. have published a public catalogue of voids in the Sloan Digital Sky Survey Data Release 7 main galaxy and luminous red galaxy samples, using the void-finding algorithm ZOBOV, which is based on the watershed transform. We examine the properties of this catalogue and show that it suffers from several problems and inconsistencies, including the identification of some extremely overdense regions as voids. As a result, cosmological results obtained using this catalogue need to be reconsidered. We provide instead an alternative, self-consistent, public catalogue of voids in the same galaxy data, obtained from using an improved version of the same watershed transform algorithm. We provide a more robust method of dealing with survey boundaries and masks, as well as with a radially varying selection function, which means that our method can be applied to any other survey. We discuss some basic properties of the voids thus discovered, and describe how further information may be obtained from the catalogue. In addition, we apply an inversion of the algorithm to the same data to obtain a corresponding catalogue of large-scale overdense structures, or `superclusters'. Our catalogues are available for public download on the journal website.
We present a new catalog of spectroscopically confirmed white dwarf stars from the Sloan Digital Sky Survey (SDSS) Data Release 7 spectroscopic catalog. We find 20407 white dwarf spectra, representing 19712 stars, and provide atmospheric model fits to 14120 DA and 1011 DB white dwarf spectra from 12843 and 923 stars, respectively. These numbers represent more than a factor of two increase in the total number of white dwarf stars from the previous SDSS white dwarf catalogs based on DR4 data. Our distribution of subtypes varies from previous catalogs due to our more conservative, manual classifications of each star in our catalog, supplementing our automatic fits. In particular, we find a large number of magnetic white dwarf stars whose small Zeeman splittings mimic increased Stark broadening that would otherwise result in an overestimated logg if fit as a non-magnetic white dwarf. We calculate mean DA and DB masses for our clean, non-magnetic sample and find the DB mean mass is statistically larger than that for the DAs.
We present an automated method for the detection of bar structure in optical images of galaxies using a deep convolutional neural network that is easy to use and provides good accuracy. In our study, we use a sample of 9346 galaxies in the redshift range of 0.009-0.2 from the Sloan Digital Sky Survey (SDSS), which has 3864 barred galaxies, the rest being unbarred. We reach a top precision of 94 per cent in identifying bars in galaxies using the trained network. This accuracy matches the accuracy reached by human experts on the same data without additional information about the images. Since deep convolutional neural networks can be scaled to handle large volumes of data, the method is expected to have great relevance in an era where astronomy data is rapidly increasing in terms of volume, variety, volatility, and velocity along with other V's that characterize big data. With the trained model, we have constructed a catalogue of barred galaxies from SDSS and made it available online.
The Sloan Digital Sky Survey-II Supernova Survey has identified a large number of new transient sources in a 300deg^2^ region along the celestial equator during its first two seasons of a three-season campaign. Multi-band (ugriz) light curves were measured for most of the sources, which include solar system objects, galactic variable stars, active galactic nuclei, supernovae (SNe), and other astronomical transients. The imaging survey is augmented by an extensive spectroscopic follow-up program to identify SNe, measure their redshifts, and study the physical conditions of the explosions and their environment through spectroscopic diagnostics. During the survey, light curves are rapidly evaluated to provide an initial photometric type of the SNe, and a selected sample of sources are targeted for spectroscopic observations. In the first two seasons, 476 sources were selected for spectroscopic observations, of which 403 were identified as SNe. For the type Ia SNe, the main driver for the survey, our photometric typing and targeting efficiency is 90%. Only 6% of the photometric SN Ia candidates were spectroscopically classified as non-SN Ia instead, and the remaining 4% resulted in low signal-to-noise, unclassified spectra.
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