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Register a new userSDSS quasars in the WISE preliminary data release and quasar candidate selection with optical/infrared colors
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We present a catalog of 37,842 quasars in the SDSS Data Release 7, which have counterparts within 6 in the WISE Preliminary Data Release. The overall WISE detection rate of the SDSS quasars is 86.7%, and it decreases to less than 50.0% when the quasar magnitude is fainter than $i=20.5$. We derive the median color-redshift relations based on this SDSS-WISE quasar sample and apply them to estimate the photometric redshifts of the SDSS-WISE quasars. We find that by adding the WISE W1- and W2-band data to the SDSS photometry we can increase the photometric redshift reliability, defined as the percentage of sources with the photometric and spectroscopic redshift difference less than 0.2, from 70.3% to 77.2%. We also obtain the samples of WISE-detected normal and late-type stars with SDSS spectroscopy, and present a criterion in the $z-W1$ versus $g-z$ color-color diagram, $z-W1>0.66(g-z)+2.01$, to separate quasars from stars. With this criterion we can recover 98.6% of 3089 radio-detected SDSS-WISE quasars with redshifts less than four and overcome the difficulty in selecting quasars with redshifts between 2.2 and 3 from SDSS photometric data alone. We also suggest another criterion involving the WISE color only, $W1-W2>0.57$, to efficiently separate quasars with redshifts less than 3.2 from stars. In addition, we compile a catalog of 5614 SDSS quasars detected by both WISE and UKIDSS surveys and present their color-redshift relations in the optical and infrared bands. By using the SDSS $ugriz$, UKIDSS YJHK and WISE W1- and W2-band photometric data, we can efficiently select quasar candidates and increase the photometric redshift reliability up to 87.0%. We discuss the implications of our results on the future quasar surveys. An updated SDSS-WISE quasar catalog consisting of 101,853 quasars with the recently released WISE all-sky data is also provided.
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The SDSS-III Baryon Oscillation Spectroscopic Survey (BOSS), a five-year spectroscopic survey of 10,000 deg^2, achieved first light in late 2009. One of the key goals of BOSS is to measure the signature of baryon acoustic oscillations in the distribution of Ly-alpha absorption from the spectra of a sample of ~150,000 z>2.2 quasars. Along with measuring the angular diameter distance at zapprox2.5, BOSS will provide the first direct measurement of the expansion rate of the Universe at z > 2. One of the biggest challenges in achieving this goal is an efficient target selection algorithm for quasars over 2.2 < z < 3.5, where their colors overlap those of stars. During the first year of the BOSS survey, quasar target selection methods were developed and tested to meet the requirement of delivering at least 15 quasars deg^-2 in this redshift range, out of 40 targets deg^-2. To achieve these surface densities, the magnitude limit of the quasar targets was set at g <= 22.0 or r<=21.85. While detection of the BAO signature in the Ly-alpha absorption in quasar spectra does not require a uniform target selection, many other astrophysical studies do. We therefore defined a uniformly-selected subsample of 20 targets deg^-2, for which the selection efficiency is just over 50%. This CORE subsample will be fixed for Years Two through Five of the survey. In this paper we describe the evolution and implementation of the BOSS quasar target selection algorithms during the first two years of BOSS operations. We analyze the spectra obtained during the first year. 11,263 new z>2.2 quasars were spectroscopically confirmed by BOSS. Our current algorithms select an average of 15 z > 2.2 quasars deg^-2 from 40 targets deg^-2 using single-epoch SDSS imaging. Multi-epoch optical data and data at other wavelengths can further improve the efficiency and completeness of BOSS quasar target selection. [Abridged]
Over the last decade, quasar sample sizes have increased from several thousand to several hundred thousand, thanks mostly to SDSS imaging and spectroscopic surveys. LSST, the next-generation optical imaging survey, will provide hundreds of detections per object for a sample of more than ten million quasars with redshifts of up to about seven. We briefly review optical quasar selection techniques, with emphasis on methods based on colors, variability properties and astrometric behavior.
High-redshift quasars are important tracers of structure and evolution in the early universe. However, they are very rare and difficult to find when using color selection because of contamination from late-type dwarfs. High-redshift quasar surveys based on only optical colors suffer from incompleteness and low identification efficiency, especially at $zgtrsim4.5$. We have developed a new method to select $4.7lesssim z lesssim 5.4$ quasars with both high efficiency and completeness by combining optical and mid-IR Wide-field Infrared Survey Explorer (WISE) photometric data, and are conducting a luminous $zsim5$ quasar survey in the whole Sloan Digital Sky Survey (SDSS) footprint. We have spectroscopically observed 99 out of 110 candidates with $z$-band magnitudes brighter than 19.5 and 64 (64.6%) of them are quasars with redshifts of $4.4lesssim z lesssim 5.5$ and absolute magnitudes of $-29lesssim M_{1450} lesssim -26.4$. In addition, we also observed 14 fainter candidates selected with the same criteria and identified 8 (57.1%) of them as quasars with $4.7<z<5.4$ . Among 72 newly identified quasars, 12 of them are at $5.2 < z < 5.7$, which leads to an increase of $sim$36% of the number of known quasars at this redshift range. More importantly, our identifications doubled the number of quasars with $M_{1450}<-27.5$ at $z>4.5$, which will set strong constraints on the bright end of the quasar luminosity function. We also expand our method to select quasars at $zgtrsim5.7$. In this paper we report the discovery of four new luminous $zgtrsim5.7$ quasars based on SDSS-WISE selection.
We present a catalog of quasars and corresponding redshifts in the Kilo-Degree Survey (KiDS) Data Release 4. We trained machine learning (ML) models, using optical ugri and near-infrared ZYJHK_s bands, on objects known from Sloan Digital Sky Survey (SDSS) spectroscopy. We define inference subsets from the 45 million objects of the KiDS photometric data limited to 9-band detections. We show that projections of the high-dimensional feature space can be successfully used to investigate the estimations. The model creation employs two test subsets: randomly selected and the faintest objects, which allows to fit the bias versus variance trade-off. We tested three ML models: random forest (RF), XGBoost (XGB), and artificial neural network (ANN). We find that XGB is the most robust model for classification, while ANN performs the best for combined classification and redshift. The inference results are tested using number counts, Gaia parallaxes, and other quasar catalogs. Based on these tests, we derived the minimum classification probability which provides the best purity versus completeness trade-off: p(QSO_cand) > 0.9 for r < 22 and p(QSO_cand) > 0.98 for 22 < r < 23.5. We find 158,000 quasar candidates in the safe inference subset (r < 22) and an additional 185,000 candidates in the reliable extrapolation regime (22 < r < 23.5). Test-data purity equals 97% and completeness is 94%; the latter drops by 3% in the extrapolation to data fainter by one magnitude than the training set. The photometric redshifts were modeled with Gaussian uncertainties. The redshift error (mean and scatter) equals 0.01 +/- 0.1 in the safe subset and -0.0004 +/- 0.2 in the extrapolation, in a redshift range of 0.14 < z < 3.63. Our success of the extrapolation challenges the way that models are optimized and applied at the faint data end. The catalog is ready for cosmology and active galactic nucleus (AGN) studies.
We determine the 22$mu$m luminosity evolution and luminosity function for quasars from a data set of over 20,000 objects obtained by combining flux-limited Sloan Digital Sky Survey optical and Wide field Infrared Survey Explorer mid-infrared data. We apply methods developed in previous works to access the intrinsic population distributions non-parametrically, taking into account the truncations and correlations inherent in the data. We find that the population of quasars exhibits positive luminosity evolution with redshift in the mid-infrared, but with considerably less mid-infrared evolution than in the optical or radio bands. With the luminosity evolutions accounted for, we determine the density evolution and local mid-infrared luminosity function. The latter displays a sharp flattening at local luminosities below $sim 10^{31}$ erg sec$^{-1}$ Hz$^{-1}$, which has been reported previously at 15 $mu$m for AGN classified as both type-1 and type-2. We calculate the integrated total emission from quasars at 22 $mu$m and find it to be a small fraction of both the cosmic infrared background light and the integrated emission from all sources at this wavelength.
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