Related papers: QUEST (Quasar Unsupervised Encoder and Synthesis T…

We present an empirical algorithm for obtaining photometric redshifts of quasars using 5-band Sloan Digital Sky Survey (SDSS) photometry. Our algorithm generates an empirical model of the quasar color-redshift relation, compares the colors…

This paper presents a comprehensive study of quasar photometric classification and redshift estimation using machine learning techniques. We cross-matched photometric data from the Dark Energy Survey Data Release 2 (DES DR2) with…

Broad Absorption Line Quasars (BALQSOs) displaying distinct blue-shifted broad absorption lines. These serve as invaluable probes for unraveling the intricate structure and evolution of quasars, shedding light on the profound influence…

Few-shot classification which aims to recognize unseen classes using very limited samples has attracted more and more attention. Usually, it is formulated as a metric learning problem. The core issue of few-shot classification is how to…

Slitless spectroscopy is a traditional method for selecting quasars. In this paper, we develop a procedure for selecting quasars (QSOs) using the 3D-HST G141 slitless spectra. We initially identify over 6,000 sources with emission lines…

Lensed quasars are key to many areas of study in astronomy, offering a unique probe into the intermediate and far universe. However, finding lensed quasars has proved difficult despite significant efforts from large collaborations. These…

Optical spectra of galaxies and quasars from large cosmological surveys are used to measure redshifts and infer distances. They are also rich with information on the intrinsic properties of these astronomical objects. However, their…

Large language models have achieved remarkable success but remain largely black boxes with poorly understood internal mechanisms. To address this limitation, many researchers have proposed various interpretability methods including…

We present a method of selecting quasars up to redshift $\approx$ 6 with random forests, a supervised machine learning method, applied to Pan-STARRS1 and WISE data. We find that, thanks to the increasing set of known quasars we can assemble…

Accurate redshift measurements are essential for studying the evolution of quasi-stellar objects (QSOs) and their role in cosmic structure formation. While spectroscopic redshifts provide high precision, they are impractical for the vast…

Recently, hyperspectral imaging (HSI) has attracted increasing research attention, especially for the ones based on a coded aperture snapshot spectral imaging (CASSI) system. Existing deep HSI reconstruction models are generally trained on…

This paper introduces the quantum deep sets model, expanding the quantum machine learning tool-box by enabling the possibility of learning variadic functions using quantum systems. A couple of variants are presented for this model. The…

We instantiate the quantum reservoir autoencoder (QRA) with a noise-induced reservoir employing reset noise channels and address two open problems: noise-resilient reversibility and blind decryption. For a single-ciphertext protocol with 10…

A number of deep, wide-field, near-infrared surveys employing new infrared cameras on 4m-class telescopes are about to commence. These surveys have the potential to determine the fraction of luminous dust-obscured quasars that may have…

Few-shot segmentation (FSS) aims to segment unseen classes using a few annotated samples. Typically, a prototype representing the foreground class is extracted from annotated support image(s) and is matched to features representing each…

The impressive pace of advance of quantum technology calls for robust and scalable techniques for the characterization and validation of quantum hardware. Quantum process tomography, the reconstruction of an unknown quantum channel from…

Based on the SDSS and SDSS-WISE quasar datasets, we put forward two schemes to estimate the photometric redshifts of quasars. Our schemes are based on the idea that the samples are firstly classified into subsamples by a classifier and then…

Leveraging quantum properties to enhance complex learning tasks has been proven feasible, with excellent recent achievements in the field of unsupervised learning. However, current quantum schemes neglect adaptive adjustments for…

The Event Horizon Telescope (EHT) provides an avenue to study black hole accretion flows on event-horizon scales. Fitting a semi-analytical model to EHT observations requires the construction of synthetic images, which is computationally…

The Dark Energy Spectroscopic Instrument (DESI) survey will measure large-scale structures using quasars as direct tracers of dark matter in the redshift range 0.9<z<2.1 and using Ly-alpha forests in quasar spectra at z>2.1. We present…