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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%)…

We present our first results of the survey for high redshift quasars at $5 \lesssim {\rm z} \lesssim 5.7$. The search for quasars in this redshift range has been known to be challenging due to limitations of filter sets used in previous…

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 the results of a pilot survey to find dust-reddened quasars by matching the FIRST radio catalog to the UKIDSS near-infrared survey, and using optical data from SDSS to select objects with very red colors. The deep K-band limit…

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…

Quasars are galaxies hosting accreting supermassive black holes; due to their brightness, they are unique probes of the early universe. To date, only few quasars have been reported at $z > 6.5$ ($<$800 Myr after the Big Bang). In this work,…

Understanding the faint end of quasar luminosity function at a high redshift is important since the number density of faint quasars is a critical element in constraining ultraviolet (UV) photon budgets for ionizing the intergalactic medium…

High redshift quasars ($z>5$) that also shine brightly at radio wavelengths are unique signposts of supermassive black hole activity in the early universe. However, bright radio sources at $z\ge5$ are extremely rare and therefore we have…

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…

We report the identification of 64 new candidates of compact galaxies, potentially hosting faint quasars with bolometric luminosities of $L_\mathrm{bol} = 10^{43}$--10$^{46}$ erg s$^{-1}$, residing in the reionization epoch within the…

We report the first results of a high-redshift ($z$ >~ 5) quasar survey using the Dark Energy Spectroscopic Instrument (DESI). As a DESI secondary target program, this survey is designed to carry out a systematic search and investigation of…

We present a new classification method for quasar identification in the EROS-2 and MACHO datasets based on a boosted version of Random Forest classifier. We use a set of variability features including parameters of a continuous auto…

We present a photometric method for identifying stars, galaxies and quasars in multi-color surveys, which uses a library of >65000 color templates. The method aims for extracting the information content of object colors in a statistically…

We report the discovery of four quasars with $M_{1450} \gtrsim -25.0$ mag at $z\sim5$ and supermassive black hole mass measurement for one of the quasars. They were selected as promising high-redshift quasar candidates via deep learning and…

Large-scale surveys over the last years have revealed about 300 QSOs at redshift above 6. Follow-up observations identified surprising properties, such as the very high black hole (BH) masses, spatial correlations with surrounding cold gas…

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…

We apply a convolutional neural network (CNN) to classify and detect quasars in the Sloan Digital Sky Survey Stripe 82 and also to predict the photometric redshifts of quasars. The network takes the variability of objects into account by…

We present the results of the spectroscopic follow up of the QUBRICS survey. The selection method is based on a machine learning approach applied to photometric catalogs, covering an area of $\sim$ 12,400 deg$^2$ in the Southern Hemisphere.…

We describe the algorithm for selecting quasar candidates for optical spectroscopy in the Sloan Digital Sky Survey. Quasar candidates are selected via their non-stellar colors in "ugriz" broad-band photometry, and by matching unresolved…

We conduct a pilot investigation to determine the optimal combination of color and variability information to identify quasars in current and future multi-epoch optical surveys. We use a Bayesian quasar selection algorithm (Richards et al.…