Related papers: Random Forests as a viable method to select and di…

The Wide-Area VISTA Extragalactic Survey (WAVES) on the 4-metre Multi-Object Spectroscopic Telescope (4MOST) includes two flux-limited subsurveys with very high (95\%) completeness requirements: Wide over $\sim\!1200$ deg$^2$ and Deep over…

We present the discovery of two z > 6 quasars, selected as i band dropouts in the VST ATLAS survey. Our first quasar has redshift, z = 6.31 \pm 0.03, z band magnitude, z_AB = 19.63 \pm 0.08 and rest frame 1450A absolute magnitude, M_1450 =…

The identification of bright quasars at z>6 enables detailed studies of supermassive black holes, massive galaxies, structure formation, and the state of the intergalactic medium within the first billion years after the Big Bang. We present…

We present the discovery and spectroscopic confirmation with the ESO NTT and Gemini South telescopes of eight new 6.0 < z < 6.5 quasars with z$_{AB}$ < 21.0. These quasars were photometrically selected without any star-galaxy morphological…

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…

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…

Random forests are a learning algorithm proposed by Breiman [Mach. Learn. 45 (2001) 5--32] that combines several randomized decision trees and aggregates their predictions by averaging. Despite its wide usage and outstanding practical…

We present spectroscopy of binary quasar candidates selected from Data Release 4 of the Sloan Digital Sky Survey (SDSS DR4) using Kernel Density Estimation (KDE). We present 27 new sets of observations, 10 of which are binary quasars,…

The WISE satellite has detected hundreds of millions sources over the entire sky. Classifying them reliably is however a challenging task due to degeneracies in WISE multicolour space and low levels of detection in its two…

Recently, it was suggested that large concentrations or groups of quasars may trace sites of enhanced matter density at medium and high redshifts analogous to how galaxy clusters trace them in nearby space. We have checked existing quasar…

Random Forest (RF) is a widely used ensemble learning technique known for its robust classification performance across diverse domains. However, it often relies on hundreds of trees and all input features, leading to high inference cost and…

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 a quasar candidate identification technique based on multicolor photometry. The traditional multi-dimensional method (2 $\times$ N dimensions, where N is the number of the color-color diagrams) is reduced to a one-dimensional…

The advent of massive broad-band photometric surveys enabled photometric redshift estimates for unprecedented numbers of galaxies and quasars. These estimates can be improved using better algorithms or by obtaining complementary data such…

We describe redMaPPer, a new red-sequence cluster finder specifically designed to make optimal use of ongoing and near-future large photometric surveys. The algorithm has multiple attractive features: (1) It can iteratively self-train the…

We have used the KPNO 4-meter Mayall telescope to image 0.83 square degrees of sky in six fields at high galactic latitude in six filters spanning 3000-10000\AA\ to magnitude limits ranging from 22.1 to 23.8. As a first use of this…

Accurate estimation of photometric redshifts (photo-$z$) is crucial in studies of both galaxy evolution and cosmology using current and future large sky surveys. In this study, we employ Random Forest (RF), a machine learning algorithm, to…

We present new spectroscopic data in the field of five high-redshift (z>=0.6) candidate galaxy clusters, drawn from the EIS Cluster Candidate Catalog. A total of 327 spectra were obtained using FORS1 at the VLT, out of which 266 are…

It was recently demonstrated that two machine-learning architectures, reservoir computing and time-delayed feed-forward neural networks, can be exploited for detecting the Earth's anomaly magnetic field immersed in overwhelming complex…

We aim to increase the limited number of quasars behind M31, necessary for probing the chemical content of the gas and for proper motion reference, with reliable and homogeneous redshift measurements from emission lines. We carried out…