Related papers: Optimal strategies for identifying quasars in DESI

Estimating redshift is a central task in astrophysics, but its measurement is costly and time-consuming. In addition, current image-based methods are often validated on homogeneous datasets. The development and comparison of networks able…

We present the VST ATLAS Quasar Survey, consisting of $\sim1,229,000$ quasar (QSO) candidates with $16<g<22.5$ over $\sim4700$ deg$^2$. The catalogue is based on VST ATLAS$+$NEOWISE imaging surveys and aims to reach a QSO sky density of…

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…

Of the hundreds of $z\gtrsim6$ quasars discovered to date, only one is known to be gravitationally lensed, despite the high lensing optical depth expected at $z\gtrsim6$. High-redshift quasars are typically identified in large-scale surveys…

We present WISE All-Sky mid-infrared (IR) survey detections of 55% (17/31) of the known QSOs at z>6 from a range of surveys: the SDSS, the CFHT-LS, FIRST, Spitzer and UKIDSS. The WISE catalog thus provides a substantial increase in the…

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 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,…

We report the results of the STRong lensing Insights from the Dark Energy Survey (STRIDES) follow-up campaign of the late 2017/early 2018 season. We obtained spectra of 65 lensed quasar candidates either with EFOSC2 on the NTT or ESI on…

We apply instance-based machine learning in the form of a k-nearest neighbor algorithm to the task of estimating photometric redshifts for 55,746 objects spectroscopically classified as quasars in the Fifth Data Release of the Sloan Digital…

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…

The ability to discover new transients via image differencing without direct human intervention is an important task in observational astronomy. For these kind of image classification problems, machine Learning techniques such as…

In this work, we enhance the FNet, a 1-dimensional convolutional neural network (CNN) with a residual neural network (ResNet) architecture, to perform spectral classification of quasars, galaxies, stars, and broad absorption line…

I describe two novel techniques originally devised to select strongly lensed quasar candidates in wide-field surveys. The first relies on outlier selection in optical and mid-infrared magnitude space; the second combines mid-infrared colour…

Multiple color selection techniques have been successful in identifying quasars from wide-field broad-band imaging survey data. Among the quasars that have been discovered so far, however, there is a redshift gap at $5 \lesssim {\rm z}…

We have undertaken a survey of archived, pointed ROSAT PSPC data for blazars by correlating the ROSAT WGACAT database with several publicly available radio catalogs, restricting our candidate list to serendipitous flat radio spectrum…

Hyperspectral image (HSI) classification is a crucial technique for remote sensing to build large-scale earth monitoring systems. HSI contains much more information than traditional visual images for identifying the categories of land…

Hyperspectral image (HSI) classification is a cornerstone of remote sensing, enabling precise material and land-cover identification through rich spectral information. While deep learning has driven significant progress in this task, small…

Large amount of image denoising literature focuses on single channel images and often experimentally validates the proposed methods on tens of images at most. In this paper, we investigate the interaction between denoising and…

One-to-one label assignment in object detection has successfully obviated the need for non-maximum suppression (NMS) as postprocessing and makes the pipeline end-to-end. However, it triggers a new dilemma as the widely used sparse queries…

The Dark Energy Spectroscopic Instrument (DESI) survey will measure spectroscopic redshifts for millions of galaxies across roughly $14,000 \, \mathrm{deg}^2$ of the sky. Cross-correlating targets in the DESI survey with complementary…