Related papers: Photometric Classification of quasars from RCS-2 u…

We obtained medium-resolution spectra of 336 quasar candidates in the COSMOS HST/Treasury field using the MMT 6.5-meter telescope and the Hectospec multi-object spectrograph. Candidates were drawn from the Sloan Digital Sky Survey (SDSS)…

We present a study of variable faint optical sources discovered by comparing the Sloan Digital Sky Survey (SDSS) and the Palomar Observatory Sky Survey (POSS) catalogs. We use SDSS measurements to photometrically recalibrate several…

We combine deep, wide-field near-IR and optical imaging to demonstrate a reddening-independent quasar selection technique based on identifying outliers in the (g-z) / (z-H) colour diagram. In three fields covering a total of ~0.7 deg^2 to a…

Upcoming surveys such as Euclid, the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) and the Nancy Grace Roman Telescope (Roman) will detect hundreds of high-redshift (z > 7) quasars, but distinguishing them from the…

We introduce a probabilistic approach to select 6<z<8 quasar candidates for spectroscopic follow-up, which is based on density estimation in the high-dimensional space inhabited by the optical and near-infrared photometry. Density…

With the availability of multiwavelength, multiscale and multiepoch astronomical catalogues, the number of features to describe astronomical objects has increases. The better features we select to classify objects, the higher the…

We present a photometric method for identifying stars, galaxies and quasars in multi-color surveys and estimating multi-color redshifts for the extragalactic objects. We use a library of >65000 color templates for comparison with observed…

This paper proposes a multi-spectral random forest classifier with suitable feature selection and masking for tree cover estimation in urban areas. The key feature of the proposed classifier is filtering out the built-up region using…

This paper explores the application of machine learning methods for classifying astronomical sources using photometric data, including normal and emission line galaxies (ELGs; starforming, starburst, AGN, broad line), quasars, and stars. We…

The results of a large area, ~600 deg^2, K-band flux-limited spectroscopic survey for luminous quasars are presented. The survey utilises the UKIRT Infrared Deep Sky Survey (UKIDSS) Large Area Survey (LAS) in regions of sky within the Sloan…

Obtaining accurate photometric redshift estimations is an important aspect of cosmology, remaining a prerequisite of many analyses. In creating novel methods to produce redshift estimations, there has been a shift towards using machine…

Context. Quasars are spatially stationary, and they are essential objects in astrometry when defining reference frames. However, the census of quasars is far from complete. Mid-infared colors can be used to find quasar candidates because…

We present the results of the Extremely Luminous Quasar Survey in the $3\pi$ survey of the Panoramic Survey Telescope and Rapid Response System (Pan-STARRS; PS1). This effort applies the successful quasar selection strategy of the Extremely…

We use a multi-color classification method introduced by Wolf, Meisenheimer & Roeser (2000) to reliably identify stars, galaxies and quasars in the up to 16-dimensional color space provided by the filter set of the Calar Alto Deep Imaging…

Quasars are very important in materializing the reference frame. The excess emission of AGNs (active galactic nuclei) in the mid infrared band can be used to identify quasar candidates. As extremely distant and point like objects, quasars…

A population of quasars at z ~ 2 is determined based on dust luminosities vLv(7.8 um) that includes unobscured, partially obscured, and obscured quasars. Quasars are classified by the ratio vLv(0.25 um)/vLv(7.8 um) = UV/IR, assumed to…

We present a list of quasar candidates including photometric redshift estimates from the miniJPAS Data Release constructed using SQUEzE. This work is based on machine-learning classification of photometric data of quasar candidates using…

We present a star/galaxy classification for the Southern Photometric Local Universe Survey (S-PLUS), based on a Machine Learning approach: the Random Forest algorithm. We train the algorithm using the S-PLUS optical photometry up to $r$=21,…

We present a novel method for the optimal selection of quasars using time-series observations in a single photometric bandpass. Utilizing the damped random walk model of Kelly et al. (2009), we parameterize the ensemble quasar structure…

We have used the KPNO 4-meter Mayall telescope to image 0.83 square degrees of sky in six fields at high galactic latitude in six filters spanning 3000-10000\AA\ to magnitude limits ranging from 22.1 to 23.8. As a first use of this…