Related papers: Quasar Candidate Multicolor Selection Technique: a…
Periodically variable quasars have been suggested as close binary supermassive black holes. We present a systematic search for periodic light curves in 625 spectroscopically confirmed quasars with a median redshift of 1.8 in a 4.6 deg$^2$…
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%…
We present initial results from the first systematic survey of luminous $z\sim 5.5$ quasars. Quasars at $z \sim$ 5.5, the post-reionization epoch, are crucial tools to explore the evolution of intergalactic medium, quasar evolution and the…
Over the last two decades, around 300 quasars have been discovered at $z\gtrsim6$, yet only one has identified as being strongly gravitationally lensed. We explore a new approach -- enlarging the permitted spectral parameter space, while…
As spectroscopic surveys continue to grow in size, the problem of classifying spectra targeted as quasars (QSOs) will need to move beyond its historical reliance on human experts. Instead, automatic classifiers will increasingly become the…
Millimetre-band scans of the frequency space towards optically dim quasars is potentially a highly efficient method for detecting new high redshift molecular absorption systems. Here we describe scans towards 7 quasars over wide bandwidths…
Gravitationally lensed quasars are useful for studying astrophysics and cosmology, and enlarging the sample size of lensed quasars is important for multiple studies. In this work, we develop a lens search algorithm for four-image (quad)…
This paper describes the methodology currently being implemented in the EIS pipeline for analysing optical/infrared multi-colour data. The aim is to identify different classes of objects as well as possible undesirable features associated…
Difference imaging provides a new way to discover gravitationally lensed quasars because few non-lensed sources will show spatially extended, time variable flux. We test the method on lens candidates in the Sloan Digital Sky Survey (SDSS)…
Extreme deconvolution (XD) of broad-band photometric data can both separate stars from quasars and generate probability density functions for quasar redshifts, while incorporating flux uncertainties and missing data. Mid-infrared…
We have compiled a catalog of 903 candidates for type 1 quasars at redshifts 3<z<5.5 selected among the X-ray sources of the serendipitous XMM-Newton survey presented in the 3XMM-DR4 catalog (the median X-ray flux is 5x10^{-15} erg/s/cm^2…
Several methods exist to convert near-infrared (NIR) stellar observations into extinction maps. We present a new method based on NIR multiband observations. The method uses a discretised version of the distribution of intrinsic stellar…
We analyze the counts of low-redshift quasar candidates selected using nine-epoch SDSS imaging data. The co-added catalogs are more than 1 mag deeper than single-epoch SDSS data, and allow the selection of low-redshift quasar candidates…
We present a catalog of 100,563 unresolved, UV-excess (UVX) quasar candidates to g=21 from 2099 deg^2 of the Sloan Digital Sky Survey (SDSS) Data Release One (DR1) imaging data. Existing spectra of 22,737 sources reveals that 22,191 (97.6%)…
The identification of physically associated kiloparsec-scale quasar pairs is important for understanding galaxy evolution, the growth of supermassive black holes, and their co-evolution with host galaxies. However, their rarity and the high…
The massive photometric data collected from multiple large-scale sky surveys offer significant opportunities for measuring distances of celestial objects by photometric redshifts. However, catastrophic failure is still an unsolved problem…
In the Sloan Digital Sky Survey (SDSS) quasars are targeted using colors and anything that can cause the identifying characteristics of the colors to disappear can create problems in the source selection process. Quasar spectra contain…
MLPQNA stands for Multi Layer Perceptron with Quasi Newton Algorithm and it is a machine learning method which can be used to cope with regression and classification problems on complex and massive data sets. In this paper we give the…
We present a new method for quasar target selection using photometric fluxes and a Bayesian probabilistic approach. For our purposes we target quasars using Sloan Digital Sky Survey (SDSS) photometry to a magnitude limit of g=22. The…
Machine learning techniques, specifically the k-nearest neighbour algorithm applied to optical band colours, have had some success in predicting photometric redshifts of quasi-stellar objects (QSOs): Although the mean of differences between…