Related papers: Multi-color Classification in the Calar Alto Deep …

We present the proof-of-concept of a method to find strongly lensed quasars using their spatially-extended photometric variability through difference imaging in cadenced imaging survey data. We apply the method to Pan-STARRS, starting with…

We present detailed clustering measurements for a flux limited sample of 14,000 quasars extracted from the 2dF QSO Redshift Survey (2QZ) in the redshift range 0.8<z<2.1. After splitting the sample into three redshift bins and each of them…

A number of deep, wide-field, near-infrared surveys employing new infrared cameras on 4m-class telescopes are about to commence. These surveys have the potential to determine the fraction of luminous dust-obscured quasars that may have…

We have conducted an optical/near-infrared study of the environments of radio-loud quasars (RLQs) at redshifts z=0.6-2. In this paper we discuss the sample selection and observations for the z=1-2 subsample and the reduction and cataloguing…

We explore the accuracy of the clustering-based redshift inference within the MICE2 simulation. This method uses the spatial clustering of galaxies between a spectroscopic reference sample and an unknown sample. The goal of this study is to…

We present a catalog of over 130,000 quasars candidates with NIR photometric properties, with an areal coverage of approximately 1,200 deg^2. This is achieved by matching the Sloan Digital Sky Survey (SDSS) in the optical ugriz bands, to…

We report the result of a faint quasar survey in a one square degree field. The aim is to test the Y-K/g-z and J-K/i-Y color selection criteria for quasars at faint magnitude, to obtain a complete sample of quasars based on deep optical and…

We make available in electronic form the stellar catalog of 19,494 objects from the Deep Multicolor Survey (DMS). The DMS is based on CCD imaging with the Mayall 4-m telescope in U,B,V,R',I75,I86 and covers 0.83 sq. deg. in six fields at…

We report the discovery of 31 new redshifted broad absorption line quasars (RSBALs) from the Sloan Digital Sky Survey (SDSS). The number of previously known such objects is 19. The identification of the new objects was enabled by…

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)…

Photometric redshift classifiers provide a means of estimating galaxy redshifts from observations using a small number of broad-band filters. However, the accuracy with which redshifts can be determined is sensitive to the star formation…

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…

We present an algorithm for selecting an uniform sample of gravitationally lensed quasar candidates from low-redshift (0.6<z<2.2) quasars brighter than i=19.1 that have been spectroscopically identified in the SDSS. Our algorithm uses…

The clustering of quasars on small scales yields fundamental constraints on models of quasar evolution and the buildup of supermassive black holes. This paper describes the first systematic survey to discover high redshift binary quasars.…

In any computer vision task involving color images, a necessary step is classifying pixels according to color and segmenting the respective areas. However, the development of methods able to successfully complete this task has proven…

Thanks to incredible advances in instrumentation, surveys like the Sloan Digital Sky Survey have been able to find and catalog billions of objects, ranging from local M dwarfs to distant quasars. Machine learning algorithms have greatly…

The upcoming galaxy large-scale surveys, such as the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST), will generate photometry for billions of galaxies. The interpretation of large-scale weak lensing maps, as well as the…

Photometric redshifts have proven a powerful tool in identifying galaxies over a large range of lookback times. We have been generalising this technique to incorporate the selection of candidate high redshift QSOs. We have applied this to a…

In this paper, the fourth version the Sloan Digital Sky Survey (SDSS-4), Data Release 16 dataset was used to classify the SDSS dataset into galaxies, stars, and quasars using machine learning and deep learning architectures. We efficiently…

Quasar redshifts require the best possible precision and accuracy for a number of applications, such as setting the velocity scale for outflows as well as measuring small-scale quasar-quasar clustering. The most reliable redshift standard…