SDSS absolute magnitudes for thin-disc stars based on trigonometric parallaxes

We present a new luminosity–colour relation based on trigonometric parallaxes for thin-disc main-sequence stars in Sloan Digital Sky Survey (SDSS) photometry. We matched stars from the newly reduced Hipparcos catalogue with the ones taken from Two-Micron All-Sky Survey (2MASS) All-Sky Catalogue of Point Sources, and applied a series of constraints, i.e. relative parallax errors  (σ_π/π≤ 0.05)  , metallicity  (−0.30 ≤[M/H]≤ 0.20 dex)  , age  (0 ≤ t ≤ 10 Gyr)  and surface gravity  (log  g > 4)  , and obtained a sample of thin-disc main-sequence stars. Then, we used our previous transformation equations ( Bilir et al. 2008a ) between SDSS and 2MASS photometries and calibrated the   M_g   absolute magnitudes to the  ( g − r )₀  and  ( r − i )₀  colours. The transformation formulae between 2MASS and SDSS photometries along with the absolute magnitude calibration provide space densities for bright stars which saturate the SDSS magnitudes.     

Quasar candidates selection in the Virtual Observatory era

We present a method for the photometric selection of candidate quasars in multiband surveys. The method makes use of a priori knowledge derived from a subsample of spectroscopic confirmed quasi-stellar objects (QSOs) to map the parameter space. The disentanglement of QSOs candidates and stars is performed in the colour space through the combined use of two algorithms, the probabilistic principal surfaces and the negative entropy clustering, which are for the first time used in an astronomical context. Both methods have been implemented in the voneural package on the Astrogrid Virtual Observatory platform. Even though they belong to the class of the unsupervised clustering tools, the performances of the method are optimized by using the available sample of confirmed quasars and it is therefore possible to learn from any improvement in the available 'base of knowledge'. The method has been applied and tested on both optical and optical plus near-infrared data extracted from the visible Sloan Digital Sky Survey (SDSS) and infrared United Kingdom Infrared Deep Sky Survey-Large Area Survey public data bases. In all cases, the experiments lead to high values of both efficiency and completeness, comparable if not better than the methods already known in the literature. A catalogue of optical candidate QSOs extracted from the SDSS Data Release 7 Legacy photometric data set has been produced and is publicly available at the URL http://voneural.na.infn.it/qso.html .     

SDSS unveils a population of intrinsically faint cataclysmic variables at the minimum orbital period

We discuss the properties of 137 cataclysmic variables (CVs) which are included in the Sloan Digital Sky Survey (SDSS) spectroscopic data base, and for which accurate orbital periods have been measured. 92 of these systems are new discoveries from SDSS and were followed-up in more detail over the past few years. 45 systems were previously identified as CVs because of the detection of optical outbursts and/or X-ray emission, and subsequently re-identified from the SDSS spectroscopy. The period distribution of the SDSS CVs differs dramatically from that of all the previously known CVs, in particular it contains a significant accumulation of systems in the orbital period range 80–86 min. We identify this feature as the elusive 'period minimum spike' predicted by CV population models, which resolves a long-standing discrepancy between compact binary evolution theory and observations. We show that this spike is almost entirely due to the large number of CVs with very low accretion activity identified by SDSS. The optical spectra of these systems are dominated by emission from the white dwarf photosphere, and display little or no spectroscopic signature from the donor stars, suggesting very low mass companion stars. We determine the average absolute magnitude of these low-luminosity CVs at the period minimum to be  〈 M_g 〉= 11.6 ± 0.7  . Comparison of the SDSS CV sample to the CVs found in the Hamburg Quasar Survey and the Palomar Green Survey suggests that the depth of SDSS is the key ingredient resulting in the discovery of a large number of intrinsically faint short-period systems.     

Color-Redshift Relations and Photometric Redshift Estimations of Quasars in Large Sky Surveys

With a recently constructed composite quasar spectrum and the X2 minimization technique, we describe a general method for estimating the photometric redshifts of a large sample of quasars by deriving theoretical color-redshift relations and comparing the theoretical colors with the observed ones. We estimated the photometric redshifts from the 5-band SDSS photometric data of 18678 quasars in the first major data release of SDSS and compared them with their spectroscopic redshifts. The difference is less than 0.1 for 47% of the quasars and less than 0.2 for 68%. Based on the calculation of the theoretical color-color diagrams of stars, galaxies and quasars both on the SDSS system and on the BATC system, we expect that we would be able to select candidates of high redshift quasars more efficaciously with the latter than with the former, provided the BATC survey can detect objects with magnitudes fainter than 21.     

Estimating the redshift distribution of photometric galaxy samples – II. Applications and tests of a new method

In Lima et al. we presented a new method for estimating the redshift distribution,   N ( z )  , of a photometric galaxy sample, using photometric observables and weighted sampling from a spectroscopic subsample of the data. In this paper, we extend this method and explore various applications of it, using both simulations and real data from the Sloan Digital Sky Survey (SDSS). In addition to estimating the redshift distribution for an entire sample, the weighting method enables accurate estimates of the redshift probability distribution,   p ( z )  , for each galaxy in a photometric sample. Use of   p ( z )  in cosmological analyses can substantially reduce biases associated with traditional photometric redshifts, in which a single redshift estimate is associated with each galaxy. The weighting procedure also naturally indicates which galaxies in the photometric sample are expected to have accurate redshift estimates, namely those that lie in regions of photometric-observable space that are well sampled by the spectroscopic subsample. In addition to providing a method that has some advantages over standard photo- z estimates, the weights method can also be used in conjunction with photo- z estimates e.g. by providing improved estimation of   N ( z )  via deconvolution of   N ( z _phot)  and improved estimates of photo- z scatter and bias. We present a publicly available   p ( z )  catalogue for ∼78 million SDSS DR7 galaxies.     

NoSOCS in SDSS – I. Sample definition and comparison of mass estimates

We use Sloan Digital Sky Survey (SDSS) data to investigate galaxy cluster properties of the systems first detected within Digitized Second Palomar Observatory Sky Survey. With the high-quality photometry of SDSS, we derived new photometric redshifts and estimated richness and optical luminosity. For a subset of low-redshift  ( z ≤ 0.1)  clusters, we have used SDSS spectroscopic data to identify groups in redshift space in the region of each cluster, complemented with massive systems from the literature to assure the continuous mass sampling. A method to remove interlopers is applied, and a virial analysis is performed resulting in the estimates of velocity dispersion, mass and a physical radius for each low- z system. We discuss the choice of maximum radius and luminosity range in the dynamical analysis, showing that a spectroscopic survey must be complete to at least   M *+ 1  if one wishes to obtain accurate and unbiased estimates of velocity dispersion and mass. We have measured X-ray luminosity for all clusters using archival data from ROSAT All Sky Survey. For a smaller subset (21 clusters), we selected temperature measures from the literature and estimated mass from the   M − T _X  relation, finding that they show good agreement with the virial estimate. However, these two mass estimates tend to disagree with the caustic results. We measured the presence of substructure in all clusters of the sample and found that clusters with substructure have virial masses higher than those derived from T _X. This trend is not seen when comparing the caustic and X-ray masses. That happens because the caustic mass is estimated directly from the mass profile, so it is less affected by substructure.     

The 2dF-SDSS LRG and QSO Survey: the spectroscopic QSO catalogue

We present the final spectroscopic QSO catalogue from the 2dF-SDSS LRG (luminous red galaxy) and QSO (2SLAQ) survey. This is a deep,  18 < g < 21.85  (extinction corrected), sample aimed at probing in detail the faint end of the broad line active galactic nuclei luminosity distribution at   z ≲ 2.6  . The candidate QSOs were selected from SDSS photometry and observed spectroscopically with the 2dF spectrograph on the Anglo-Australian Telescope. This sample covers an area of 191.9 deg² and contains new spectra of 16 326 objects, of which 8764 are QSOs and 7623 are newly discovered [the remainder were previously identified by the 2dF QSO Redshift Survey (2QZ) and SDSS]. The full QSO sample (including objects previously observed in the SDSS and 2QZ surveys) contains 12 702 QSOs. The new 2SLAQ spectroscopic data set also contains 2343 Galactic stars, including 362 white dwarfs, and 2924 narrow emission-line galaxies with a median redshift of   z = 0.22  .
We present detailed completeness estimates for the survey, based on modelling of QSO colours, including host-galaxy contributions. This calculation shows that at   g ≃ 21.85  QSO colours are significantly affected by the presence of a host galaxy up to redshift   z ∼ 1  in the SDSS ugriz bands. In particular, we see a significant reddening of the objects in   g − i   towards the fainter g -band magnitudes. This reddening is consistent with the QSO host galaxies being dominated by a stellar population of age at least 2–3 Gyr.
The full catalogue, including completeness estimates, is available on-line at http://www.2slaq.info/ .     

M dwarfs at large heliocentric distances

We present an analysis of the faint M star population seen as foreground contaminants in deep extragalactic surveys. We use space-based data to separate such stars from high-redshift galaxies in a publicly available data set, and consider the photometric properties of the resulting sample in the optical and infrared. The inferred distances place these stars well beyond the scaleheight of the thick disc. We find strong similarities between this faint sample (reaching   i '_AB= 25  ) and the brighter disc M dwarf population studied by other authors. The optical–infrared properties of the bulk of our sources spanning 6000 Å-4.5 μm are consistent with those 5–10 mag brighter. We also present deep spectroscopy of faint M dwarf stars reaching continuum limits of i '_AB≈ 26, and measure absorption-line strengths in the CaH2 and TiO5 bands. Both photometrically and spectroscopically, our sources are consistent with metallicities as low as a tenth solar: metal-rich compared with halo stars at similar heliocentric distances. We comment on the possible massive astrophysical compact halo object (MACHO) identification of M stars at faint magnitudes.     

New faint optical spectrophotometric standards: hot white dwarfs from the Sloan Digital Sky Survey

The spectral energy distributions for pure-hydrogen (DA) hot white dwarfs can be accurately predicted by model atmospheres. This makes it possible to define spectrophotometric calibrators by scaling the theoretical spectral shapes with broad-band photometric observations – a strategy successfully exploited for the spectrographs onboard the Hubble Space Telescope ( HST ) using three primary DA standards. Absolute fluxes for non-DA secondary standards, introduced to increase the density of calibrators in the sky, need to be referred to the primary standards, but a far better solution would be to employ a network of DA stars scattered throughout the sky. We search for blue objects in the sixth data release of the Sloan Digital Sky Survey (SDSS) and fit DA model fluxes to identify suitable candidates. Reddening needs to be considered in the analysis of many of these stars. We propose a list of nine pure-hydrogen white dwarfs with absolute fluxes with estimated uncertainties below 3 per cent, including four objects with estimated errors <2 per cent, as candidates for spectrophotometric standards in the range  14 < g < 18  , and provide model-based fluxes scaled to match the SDSS broad-band fluxes for each. We apply the same method to the three HST DA standards, linking the zero point of their absolute fluxes to ugr magnitudes transformed from photometry obtained with the US Naval Observatory 1-m telescope. For these stars, we estimate uncertainties of <1 per cent in the optical, finding good consistency with the fluxes adopted for HST calibration.     

Kernel regression for determining photometric redshifts from Sloan broad-band photometry

We present a new approach, namely kernel regression, to determine photometric redshifts for 399 929 galaxies in the Fifth Data Release of the Sloan Digital Sky Survey (SDSS). Kernel regression is a weighted average of spectral redshifts of the neighbours for a query point, and higher weights are associated with points that are closer to the query point. One important design decision when using kernel regression is the choice of bandwidth. We apply 10-fold cross-validation to choose the optimal bandwidth, which is obtained as the cross-validation error approaches its minimum. The results show that the optimal bandwidth is different for different input patterns: the lowest rms error of photometric redshift estimation arrives at 0.019 using colour+eClass as the inputs, the lowest rms errors comes to 0.020 using ugriz +eClass as the inputs. Where eClass is a galaxy spectral type, and 0.021 using colour+ r as the inputs. Thus, in addition to parameters such as magnitude and colour, eClass is a valid parameter with which to predict photometric redshifts. Moreover, the results suggest that the accuracy of estimating photometric redshifts is improved when the sample is divided into early-type and late-type galaxies; in particular, for early-type galaxies, the rms scatter is 0.016 with colour+eClass as the inputs. In addition, kernel regression achieves high accuracy when predicting the photometric eClass  (σ_rms= 0.034)  using colour+ r as the input pattern. For kernel regression, the accuracy of the photometric redshifts does not always increase with the number of parameters considered, but is satisfactory only when appropriate parameters are chosen. Kernel regression is a comprehensible and accurate regression method. Experiments reveal the superiority of kernel regression over other empirical training approaches.     

The Sloan Digital Sky Survey

The Sloan Digital Sky Survey (SDSS) is going to carry out a uniform survey of π steradians of the sky in the Northern Galactic cap and ∼ 225 deg² in the Southern Hemisphere. The survey consists of a photometric and a spectroscopic survey. The SDSS will generate accurate photometry in five bands of approximately tens of millions of galaxies, tens of millions of stars and roughly a million quasars. It will also take spectra and measure redshifts of approximately a million galaxies and ten thousand quasars. The main characteristics and components of the survey are a dedicated 2.5m telescope, wide field correctors for photometry and spectroscopy that will provide a field of view of ∼ 3 degrees, a photometric camera with 30 photometric and 22 astrometric CCDs, and two fibre-fed spectrographs of 320 fibres each. The survey will produce a publicly available science database of Terabytes dimensions. This revised version was published online in July 2006 with corrections to the Cover Date.     

SDSS J121606.5+280648.5: a helium-core white dwarf in an eclipsing binary system?

A comparison of Palomar Observatory Sky Survey (POSS) and Sloan Digital Sky Survey (SDSS) images showed SDSS J121606.5+280648.5 to have increased in brightness by nearly two magnitudes since 1955. SDSS J121606.5+280648.5 turned out to be a low-mass white dwarf having a less luminous cool companion, probably a late-type Main Sequence dwarf. A possible explanation of brightening is that the companion eclipsed the white dwarf at the time the POSS plate was obtained. If SDSS J121606.5+280648.5 is an eclipsing binary, further study should help establish circumstances in which rapid mass loss occurs on the Red Giant Branch (RGB).     

Detecting active comets in the SDSS

Using a sample of serendipitously discovered active comets in the Sloan Digital Sky Survey (SDSS), we develop well-controlled selection criteria for greatly increasing the efficiency of comet identification in the SDSS catalogs. After follow-up visual inspection of images to reject remaining false positives, the total sample of SDSS comets presented here contains 19 objects, roughly one comet per 10 million other SDSS objects. The good understanding of selection effects allows a study of the population statistics, and we estimate the apparent magnitude distribution to r∼18, the ecliptic latitude distribution, and the comet distribution in SDSS color space. The most surprising results are the extremely narrow range of colors for comets in our sample (e.g. root-mean-square scatter of only ∼0.06 mag for the g-r color), and the similarity of comet colors to those of jovian Trojans. We discuss the relevance of our results for upcoming deep multi-epoch optical surveys such as the Dark Energy Survey, Pan-STARRS, and the Large Synoptic Survey Telescope (LSST), and estimate that LSST may produce a sample of about 10,000 comets over its 10-year lifetime.     

Oxygen and carbon rich cool stars in the Cepheus region: classification of selected objects from KP2001 catalogue. I

We present moderate resolution CCD spectra and R photometry for seven KP2001 stars. We revised the spectral classification of the stars in the range λλ4000−8700? . Our photometric data confirmed the behavior of the light curves downloaded from the NSVS (Northern Sky Variability Survey) database. For KP2001-32, presented as a Mira-type variable in NSVS, we estimated absolute bolometric M _b and K-band M _K magnitudes as well as the distance using the period-luminosity relations. We also estimated the mass loss rate using the calibration relations between mass loss rate and K - [12] index. From the position in infrared color-color diagrams, we confirmed the photometric classification of KP2001-221 as a semiregular variable, based on the light curve of the NSVS database. For the N-type carbon star KP2001-77 we estimated distance and absolute magnitude M _K using different calibration methods. For the remaining four objects we derived the absolute magnitudes and distances using our CCD spectra and published JHK _S magnitudes. We discuss the nature of these objects on the basis of the obtained results.     

Environmental dependence of five photometric band concentration indexes for luminous red galaxies from the SDSS Data Release 7

Using the Luminous Red Galaxy (LRG) sample of the Sloan Digital Sky Survey Data Release 7 (SDSS DR7), we explore the environmental dependence of five photometric band concentration indexes of LRGs. It turns out that the trends for all the five band concentration indexes to change with the local density are the same: galaxies with higher concentration reside preferentially in overdense environments, while galaxies with lower concentration are located preferentially in underdense environments (© 2010 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

The LAMOST spectroscopic survey of globular clusters in M31and M33.I.catalog and new identifications

We present a catalog of 908 objects observed with the Large Sky Area Multi-Object Fiber Spectroscopic Telescope(LAMOST) in fields in the vicinity of M31 and M33, targeted as globular clusters(GCs) and candidates. The targets include known GCs and candidates selected from the literature, as well as new candidates selected from the Sloan Digital Sky Survey(SDSS). Analysis shows that 356 of them are likely GCs with various confidence levels, while the remaining ones turn out to be background galaxies and quasars, stars and H II regions in M31 or foreground Galactic stars. The 356 likely GCs include 298 bona fide GCs and 26 candidates known in the literature. Three candidates, selected from the Revised Bologna Catalog of M31 GCs and candidates(RBC) and one possible cluster from Johnson et al., are confirmed to be bona fide clusters. We search for new GCs in the halo of the M31 among the new candidates selected from the SDSS photometry. Based on radial velocities yielded by LAMOST spectra and visual examination of the SDSS images, we find 28 objects, 5bona fide and 23 likely GCs. Among the five bona fide GCs, three have been recently discovered independently by others, and the remaining 25 are our new identifications,including two bona fide ones. The newly identified objects fall at projected distances ranging from 13 to 265 kpc from M31. Of the two newly discovered bona fide GCs,one is located near M33, probably a GC belonging to M33. The other bona fide GC falls on the Giant Stream with a projected distance of 78 kpc from M31. Of the 23 newly identified likely GCs, one has a projected distance of about 265 kpc from M31 and could be an intergalactic cluster.     

Oxygen abundance in giant H II galaxies

A sample of 93 emission-line high luminosity galaxies from the Sloan Digital Sky Survey (SDSS) has been investigated. Line intensities have been measured in 116 SDSS spectra. Oxygen abundance has been determined in the studied galaxies. Since the auroral line of twice ionized oxygen [O III] λ 436.3 nm cannot be detected in the spectra of the sample, the intensity ratio of nebular to auroral lines needed to determine the electron temperature is calculated using the ff-relation. The oxygen abundances obtained in SDSS high luminosity galaxies are 0.2–0.5 dex lower than the maximum attainable value. This is caused by the fact that the sample includes only the gas-rich galaxies in which intense bursts of star formation occur. The equivalent number of O7 V stars which are responsible for excitation of luminescent H II regions in the studied sample is two or three orders of magnitude more than the number of stars which cause the luminescence of the brightest H II regions in nearby galaxies, and it exceeds by one order of magnitude the number of stars which cause gas in SBS 0335-052 E to glow.     

Sample of Wolf-Rayet galaxies from the SLOAN digital sky survey

We have analyzed the spectra of blue compact dwarf galaxies from the SLOAN Digital Sky Survey (SDSS) Data Release 7 and created a sample of 271 galaxies with Wolf-Rayet (WR) spectral features produced by high-velocity stellar winds. A blue WR feature (bump) is a blend of the N V λλ 460.5 and 462.0 nm, N III λλ 463.4 and 464.0 nm, C III λ 465.0 nm, C IV λ 465.8 nm, and He II λ 468.6 nm emission lines. A red WR feature (bump) is the broad C IV λ 580.8 nm emission. The blue WR bump is mainly due to emissions of nitrogen WR (WN) stars, while the red bump is fully produced by emissions of carbon WR (WC) stars. All the sample spectra show the blue WR bumps, whereas the red WR bumps are only identified in 50% of sample spectra. We have derived the numbers of early-type WC stars (WCE) and late-type WN stars (WNL) in the galaxies using the luminosities of single WC and WN stars in the red and blue bumps, respectively. The number of O stars is estimated using the H_β luminosity. The ratio of the overall number of WR stars of different types to the number of all massive stars N(WR)/N(O + WR) decreases with decreasing metallicity, corresponding to the evolution population synthesis models.     

Automated classification of sloan digital sky survey (SDSS) stellar spectra using artificial neural networks

Automated techniques have been developed to automate the process of classification of objects or their analysis. The large datasets provided by upcoming spectroscopic surveys with dedicated telescopes urges scientists to use these automated techniques for analysis of such large datasets which are now available to the community. Sloan Digital Sky Survey (SDSS) is one of such surveys releasing massive datasets. We use Probabilistic Neural Network (PNN) for automatic classification of about 5000 SDSS spectra into 158 spectral type of a reference library ranging from O type to M type stars.