Related papers: Finding Quasars behind the Galactic Plane. I. Cand…

Machine learning techniques offer a plethora of opportunities in tackling big data within the astronomical community. We present the set of Generalized Linear Models as a fast alternative for determining photometric redshifts of galaxies, a…

We present a pipeline to identify photometric variability within strong gravitationally lensing candidates, in the DESI Legacy Imaging Surveys. In our first paper (Sheu et al. 2023), we laid out our pipeline and presented seven new…

The H.E.S.S. Galactic Plane Survey (HGPS) represents one of the most sensitive surveys of the Galactic Plane at very high energies (VHE, 0.1-100 TeV). However the source detection algorithm of the HGPS pipeline is not well-suited for…

The results of a large area, ~600 deg^2, K-band flux-limited spectroscopic survey for luminous quasars are presented. The survey utilises the UKIRT Infrared Deep Sky Survey (UKIDSS) Large Area Survey (LAS) in regions of sky within the Sloan…

We present the Multi-Array Galactic Plane Imaging Survey (MAGPIS), which maps portions of the first Galactic quadrant with an angular resolution, sensitivity and dynamic range that surpasses existing radio images of the Milky Way by more…

The hybrid quantum-classical learning scheme provides a prominent way to achieve quantum advantages on near-term quantum devices. A concrete example towards this goal is the quantum neural network (QNN), which has been developed to…

We present a catalog of nearby (z $\leq$ 0.5) quasars with significant features of post-starburst stellar populations in their optical spectra, so-called post-starburst quasars, or PSQs. After carefully decomposing spectra from the Sloan…

We present a sample of 12 quasar candidates with highly variable soft X-ray emission from the 4th XMM-newton Serendipitous Source Catalog (4XMM-DR13) using random forest. We obtained optical to mid-IR photometric data for the 4XMM-DR13…

Machine learning techniques offer a precious tool box for use within astronomy to solve problems involving so-called big data. They provide a means to make accurate predictions about a particular system without prior knowledge of the…

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…

Quasar absorption line analysis is critical for studying gas and dust components and their physical and chemical properties as well as the evolution and formation of galaxies in the early universe. Ca II absorbers, which are one of the…

We present a photometric method for identifying stars, galaxies and quasars in multi-color surveys and estimating multi-color redshifts for the extragalactic objects. We use a library of >65000 color templates for comparison with observed…

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…

Current remote sensing image classification problems have to deal with an unprecedented amount of heterogeneous and complex data sources. Upcoming missions will soon provide large data streams that will make land cover/use classification…

The UKIDSS Galactic Plane Survey (GPS) is one of the five near infrared Public Legacy Surveys that are being undertaken by the UKIDSS consortium, using the Wide Field Camera on the United Kingdom Infrared Telescope. It is surveying 1868…

Machine learning is a powerful technique, becoming increasingly popular in astrophysics. In this paper, we apply machine learning to more than a thousand globular cluster (GC) models simulated as part of the 'MOCCA-Survey Database I'…

We present a sample of 305 QSO candidates having $|b| < 30^{\circ}$, the majority with GALEX magnitudes NUV < 18.75. To generate this sample, we apply UV-IR color selection criteria to photometric data from the Ultraviolet GAlactic Plane…

Pulsar searching is essential for the scientific research in the field of physics and astrophysics. As the development of the radio telescope, the exploding volume and it growth speed of candidates growth have brought about several…

Machine learning has become widely used in astronomy. Gaussian Process (GP) regression in particular has been employed a number of times to fit or re-sample supernova (SN) light-curves, however by their nature typical GP models are not…

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…