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Automatic source detection and classification tools based on machine learning (ML) algorithms are growing in popularity due to their efficiency when dealing with large amounts of data simultaneously and their ability to work in multidimensional parameter spaces. In this work, we present a new, automated method of outlier selection based on support vector machine (SVM) algorithm called one-class SVM (OCSVM), which uses the training data as one class to construct a model of normality in order to recognize novel points. We test the performance of OCSVM algorithm on textit{Wide-field Infrared Survey Explorer (WISE)} data trained on the Sloan Digital Sky Survey (SDSS) sources. Among others, we find $sim 40,000$ sources with abnormal patterns which can be associated with obscured and unobscured active galactic nuclei (AGN) source candidates. We present the preliminary estimation of the clustering properties of these objects and find that the unobscured AGN candidates are preferentially found in less massive dark matter haloes ($M_{DMH}sim10^{12.4}$) than the obscured candidates ($M_{DMH}sim 10^{13.2}$). This result contradicts the unification theory of AGN sources and indicates that the obscured and unobscured phases of AGN activity take place in different evolutionary paths defined by different environments.
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We present the results of a new, deeper, and complete search for high-redshift $6.5<z<9.3$ quasars over 977deg$^2$ of the VISTA Kilo-Degree Infrared Galaxy (VIKING) survey. This exploits a new list-driven dataset providing photometry in all bands ZYJHKs, for all sources detected by VIKING in $J$. We use the Bayesian model comparison (BMC) selection method of Mortlock et al., producing a ranked list of just 21 candidates. The sources ranked 1, 2, 3 and 5 are the four known $z>6.5$ quasars in this field. Additional observations of the other 17 candidates, primarily DESI Legacy Survey photometry and ESO FORS2 spectroscopy, confirm that none is a quasar. This is the first complete sample from the VIKING survey, and we provide the computed selection function. We include a detailed comparison of the BMC method against two other selection methods: colour cuts and minimum-$chi^2$ SED fitting. We find that: i) BMC produces eight times fewer false positives than colour cuts, while also reaching 0.3 mag. deeper, ii) the minimum-$chi^2$ SED fitting method is extremely efficient but reaches 0.7 mag. less deep than the BMC method, and selects only one of the four known quasars. We show that BMC candidates, rejected because their photometric SEDs have high $chi^2$ values, include bright examples of galaxies with very strong [OIII]$lambdalambda$4959,5007 emission in the $Y$ band, identified in fainter surveys by Matsuoka et al. This is a potential contaminant population in Euclid searches for faint $z>7$ quasars, not previously accounted for, and that requires better characterisation.
Accurate statistical measurement with large imaging surveys has traditionally required throwing away a sizable fraction of the data. This is because most measurements have have relied on selecting nearly complete samples, where variations in the composition of the galaxy population with seeing, depth, or other survey characteristics are small. We introduce a new measurement method that aims to minimize this wastage, allowing precision measurement for any class of stars or galaxies detectable in an imaging survey. We have implemented our proposal in Balrog, a software package which embeds fake objects in real imaging in order to accurately characterize measurement biases. We demonstrate this technique with an angular clustering measurement using Dark Energy Survey (DES) data. We first show that recovery of our injected galaxies depends on a wide variety of survey characteristics in the same way as the real data. We then construct a flux-limited sample of the faintest galaxies in DES, chosen specifically for their sensitivity to depth and seeing variations. Using the synthetic galaxies as randoms in the standard Landy-Szalay correlation function estimator suppresses the effects of variable survey selection by at least two orders of magnitude. With this correction, our measured angular clustering is found to be in excellent agreement with that of a matched sample drawn from much deeper, higher-resolution space-based Cosmological Evolution Survey (COSMOS) imaging; over angular scales of $0.004^{circ} < theta < 0.2^{circ}$, we find a best-fit scaling amplitude between the DES and COSMOS measurements of $1.00 pm 0.09$. We expect this methodology to be broadly useful for extending the statistical reach of measurements in a wide variety of coming imaging surveys.
Strong gravitationally lensed quasars provide powerful means to study galaxy evolution and cosmology. We use Chitah to hunt for new lens systems in the Hyper Suprime$-$Cam Subaru Strategic Program (HSC SSP) S16A. We present 46 lens candidates, of which 3 are previously known. Including 2 additional lenses found by YattaLens, we obtain X-shooter spectra of 6 promising candidates for lens confirmation and redshift measurements. We report new spectroscopic redshift measurements for both the lens and source galaxies in 4 lens systems. We apply the lens modeling software Glee to model our 6 X-shooter lenses uniformly. Through our analysis of the HSC images, we find that HSCJ022622$-$042522, HSCJ115252$+$004733, and HSCJ141136$-$010216 have point-like lensed images, and that the lens light distribution is well aligned with mass distribution within 6 deg. Thanks to the X-shooter spectra, we estimate fluxes on the Baldwin- Phillips-Terlevich (BPT) diagram, and find that HSCJ022622$-$042522 has a probable quasar source, based on the upper limit of the Nii flux intensity. We also measure the FWHM of Ly$alpha$ emission of HSCJ141136$-$010216 to be $sim$254 km/s, showing that it is a probable Lyman-$alpha$ emitter.
The Kilo Degree Survey (KiDS) is a 1500 square degree optical imaging survey with the recently commissioned OmegaCAM wide-field imager on the VLT Survey Telescope (VST). A suite of data products will be delivered to ESO and the community by the KiDS survey team. Spread over Europe, the KiDS team uses Astro-WISE to collaborate efficiently and pool hardware resources. In Astro-WISE the team shares, calibrates and archives all survey data. The data-centric architectural design realizes a dynamic live archive in which new KiDS survey products of improved quality can be shared with the team and eventually the full astronomical community in a flexible and controllable manner
Extremely metal-poor (XMP) galaxies are defined to have gas-phase metallicity smaller than a tenth of the solar value (12 + log[O/H] < 7.69). They are uncommon, chemically and possibly dynamically primitive, with physical conditions characteristic of earlier phases of the Universe. We search for new XMPs in the Sloan Digital Sky Survey (SDSS) in a work that complements Paper I. This time high electron temperature objects are selected; since metals are a main coolant of the gas, metal- poor objects contain high-temperature gas. Using the algorithm k-means, we classify 788677 spectra to select 1281 galaxies having particularly intense [OIII]4363 with respect to [OIII]5007, which is a proxy for high electron temperature. The metallicity of these candidates was computed using a hybrid technique consistent with the direct method, rendering 196 XMPs. A less restrictive noise constraint provides a larger set with 332 candidates. Both lists are provided in electronic format. The selected XMP sample have mean stellar mass around 10^8Msun, with dust-mass sim 10^3Msun for typical star-forming regions. In agreement with previous findings, XMPs show a tendency to be tadpole-like or cometary. Their underlying stellar continuum corresponds to a fairly young stellar population (< 1Gyr), although young and aged stellar populations co-exists at the low-metallicity starbursts. About 10% of the XMPs shows large N/O. Based on their location in constrained cosmological numerical simulations, XMPs have a strong tendency to appear in voids and to avoid galaxy clusters. The puzzling 2%-solar low-metallicity threshold exhibited by XMPs remains.
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