Related papers: Quasar Selection Based on Photometric Variability

We present a new and simple technique for selecting extensive, complete and pure quasar samples, based on their intrinsic variability. We parametrize the single-band variability by a power-law model for the light-curve structure function,…

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.…

We model the time variability of ~9,000 spectroscopically confirmed quasars in SDSS Stripe 82 as a damped random walk. Using 2.7 million photometric measurements collected over 10 years, we confirm the results of Kelly et al. (2009) and…

We measure quasar variability using the Panoramic Survey Telescope and Rapid Response System 1 Survey (Pan-STARRS1 or PS1) and the Sloan Digital Sky Survey (SDSS) and establish a method of selecting quasars via their variability in 10,000…

In this work we train three decision-tree based ensemble machine learning algorithms (Random Forest Classifier, Adaptive Boosting and Gradient Boosting Decision Tree respectively) to study quasar selection in the variable source catalog in…

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 provide a quantitative description and statistical interpretation of the optical continuum variability of quasars. The Sloan Digital Sky Survey (SDSS) has obtained repeated imaging in five UV-to-IR photometric bands for 33,881…

We present a new approach to analysing the dependence of quasar variability on rest-frame wavelengths. We exploited the spectral archive of the Sloan Digital Sky Survey (SDSS) to create a sample of more than 9000 quasars in the Stripe 82.…

We use a sample of 3791 quasars from the Sloan Digital Sky Survey (SDSS) Early Data Release (EDR), and compare their photometry to historic plate material for the same set of quasars in order to study their variability properties. The time…

We compare quasar selection techniques based on their optical variability using data from the Catalina Real-time Transient Survey (CRTS). We introduce a new technique based on Slepian wavelet variance (SWV) that shows comparable or better…

We present an improved photometric error analysis for the 7,100 CRTS (Catalina Real-Time Transient Survey) optical light curves for quasars from the SDSS (Sloan Digital Sky Survey) Stripe 82 catalogue. The SDSS imaging survey has provided a…

The SDSS-III BOSS Quasar survey will attempt to observe z>2.15 quasars at a density of at least 15 per square degree to yield the first measurement of the Baryon Acoustic Oscillations in the Ly-alpha forest. To help reaching this goal, we…

Significant progress in the description of quasar variability has been recently made by employing SDSS and POSS data. Common to most studies is a fundamental assumption that photometric observations at two epochs for a large number of…

Quasars are variable and their variability can both constrain their physical properties and help to identify them. We look for ways to efficiently identify quasars exhibiting consistent variability over multi-year time-scales, based on a…

We use the Panoramic Survey Telescope and Rapid Response System 1 Survey (Pan-STARRS1, PS1) data to extend the Sloan Digital Sky Survey (SDSS) Stripe 82 quasar light curves. Combining PS1 and SDSS light curves provides a 15 yr baseline for…

We explore the multidimensional, multiwavelength selection of quasars from mid-IR (MIR) plus optical data, specifically from Spitzer-IRAC and the Sloan Digital Sky Survey (SDSS). We apply modern statistical techniques to combined Spitzer…

Context. Large, high-dimensional astronomical surveys require efficient data analysis. Automatic fitting of lightcurve variability and machine learning may assist in identification of sources including candidate quasars. Aims. We aim to…

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 study the optical $gri$ photometric variability of a sample of 190 quasars within the SDSS Stripe 82 region that have long-term photometric coverage during $\sim 1998-2020$ with SDSS, PanSTARRS-1, the Dark Energy Survey, and dedicated…

We present a catalog of 1,172,157 quasar candidates selected from the photometric imaging data of the Sloan Digital Sky Survey (SDSS). The objects are all point sources to a limiting magnitude of i=21.3 from 8417 sq. deg. of imaging from…