Related papers: Photometric classification of QSOs from ALHAMBRA s…
Although the $\Lambda$ Cold Dark Matter model is the most accredited cosmological model, information at high redshifts ($z$) between type Ia supernovae ($z=2.26$) and the Cosmic Microwave Background ($z=1100$) is crucial to validate this…
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…
Compared with raw images, the more common JPEG images are less useful for machine vision algorithms and professional photographers because JPEG-sRGB does not preserve a linear relation between pixel values and the light measured from the…
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,…
Our goal is to characterise the dependence of the optical mass-to-light ratio on galaxy colour up to z = 1.5, expanding the redshift range explored in previous work. From the ALHAMBRA redshifts, stellar masses, and rest-frame luminosities…
Random Forests (RF) is a popular machine learning method for classification and regression problems. It involves a bagging application to decision tree models. One of the primary advantages of the Random Forests model is the reduction in…
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…
The UV radiation from high redshift quasars causes a local deficit in the neutral hydrogen absorption (Lyman-alpha forest) in their spectra, known as the proximity effect. Measurements from small samples of tens to hundreds of quasars have…
Image understanding is an important research domain in the computer vision due to its wide real-world applications. For an image understanding framework that uses the Bag-of-Words model representation, the visual codebook is an essential…
Given multiband photometric data from the SDSS DR6, we estimate galaxy redshifts. We employ a Random Forest trained on color features and spectroscopic redshifts from 80,000 randomly chosen primary galaxies yielding a mapping from color to…
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…
The third Gaia Data Release has provided the astronomical community with astrometric data of more than 1.8 billion sources, and low resolution spectra for 220 million. Such a large amount of data is difficult to handle by means of visual…
We applied three statistical classification techniques - linear discriminant analysis (LDA), logistic regression and random forests - to three astronomical datasets associated with searches for interstellar masers. We compared the…
The second mission of the NASA Kepler satellite, K2, has collected hundreds of thousands of lightcurves for stars close to the ecliptic plane. This new sample could increase the number of known pulsating stars and then improve our…
We present J-H-K' photometry for a sample of 45 high redshift quasars found by the Sloan Digital Sky Survey. The sample was originally selected on the basis of optical colors and spans a redshift range from 3.6 to 5.03. Our photometry…
We simulate multi-color surveys, which use the same telescope time on different filter sets of broad-band and medium-band filters. We use a photometric classification method for identifying stars, galaxies and quasars and for estimating…
This paper presents a catalogue of optimised pointings for differential photometry of 23,779 quasars extracted from the Sloan Digital Sky Survey (SDSS) Catalogue and a score for each indicating the quality of the Field of View (FoV)…
We present an unsupervised machine learning approach that can be employed for estimating photometric redshifts. The proposed method is based on a vector quantization approach called Self--Organizing Mapping (SOM). A variety of…
The goal of the present paper is to assess the usefulness of quasars as cosmological distance indicators. We calibrate, in a model-independent way, the non-linear relation between X-ray and UV emission to derive quasar luminosity distances.…
The wavelength dependence of atmospheric refraction causes differential chromatic refraction (DCR), whereby objects imaged at different optical/UV wavelengths are observed at slightly different positions in the plane of the detector. Strong…