Related papers: Applications of Machine Learning Algorithms In Pro…
Low-frequency radio data improve the sensitivity of pulsar timing arrays (PTAs) to propagation effects such as dispersion measure (DM) variations, enabling better noise characterization essential for detecting the stochastic gravitational…
Large-scale astronomical surveys can capture numerous images of celestial objects, including galaxies and nebulae. Analysing and processing these images can reveal intricate internal structures of these objects, allowing researchers to…
The Sloan Digital Sky Survey has validated and made publicly available its Second Data Release. This data release consists of 3324 square degrees of five-band (u g r i z) imaging data with photometry for over 88 million unique objects,…
The Pan-STARRS1 survey is acquiring multi-epoch imaging in 5 bands (grizy) over the entire sky north of declination -30deg (the $3\pi$ survey). In July 2011 a test area of about 70 sq.deg. was observed to the expected final depth of the…
Astroinformatics is a new impact area in the world of astronomy, occasionally called the final frontier, where several astrophysicists, statisticians and computer scientists work together to tackle various data intensive astronomical…
The Chinese Space Station Survey Telescope (CSST) aims to map the universe across an unprecedented dynamic range of stellar densities, spanning from extragalactic voids to the crowded Galactic center (e.g. a few stars and galaxies in the…
This paper reports on the application of the supervised machine-learning algorithm to the stellar effective temperature regression for the second $Gaia$ data release, based on the combination of the stars in four spectroscopic surveys:…
In the coming decade, astronomical surveys of the sky will generate tens of terabytes of images and detect hundreds of millions of sources every night. The study of these sources will involve computation challenges such as anomaly detection…
Spectroscopic surveys are undergoing a rapid expansion in their data collecting capabilities, reaching the level of hundreds of spectra per pointing. An efficient use of such huge amounts of information requires a high degree of…
The Einstein Telescope is a conceived third generation gravitational-wave detector that is envisioned to be an order of magnitude more sensitive than advanced LIGO, Virgo and Kagra, which would be able to detect gravitational-wave signals…
The accuracy of the estimated stellar atmospheric parameter decreases evidently with the decreasing of spectral signal-to-noise ratio (SNR) and there are a huge amount of this kind observations, especially in case of SNR$<$30. Therefore, it…
From investigating molecular vibrations to observing galaxies, terahertz technology has found extensive applications in research and development over the past three decades. Terahertz time-domain spectroscopy and imaging have experienced…
The range to which the Laser Interferometer Gravitational-Wave Observatory (LIGO) can observe astrophysical systems varies over time, limited by noise in the instruments and their environments. Identifying and removing the sources of noise…
The LOFAR Two-metre Sky Survey (LoTSS) is an ongoing sensitive, high-resolution 120-168MHz survey of the entire northern sky for which observations are now 20% complete. We present our first full-quality public data release. For this data…
We investigate the role of asymmetries in the line spread function of the 2-degree field spectrograph and the variations in these asymmetries with the CCD, the plate, the time of observation and the fibre. A data-reduction pipeline is…
In this study, the fundamental stellar atmospheric parameters (Teff, log g, [Fe/H] and [{\alpha}/Fe]) were derived for low-resolution spectroscopy from LAMOST DR5 with Generative Spectrum Networks (GSN). This follows the same scheme as a…
We present details of improvements to data processing and analysis which were recently used for a re-reduction of the Very Large Array (VLA) Low-frequency Sky Survey (VLSS) data. Algorithms described are implemented in the data-reduction…
The Galactic O-Star Spectroscopic Survey (GOSSS) is an ambitious project that is observing all known Galactic O stars with B < 13 in the blue-violet part of the spectrum with R-2500. It is based on version 2 of the most complete catalog to…
We applied machine learning to the entire data history of ESO's High Accuracy Radial Velocity Planet Searcher (HARPS) instrument. Our primary goal was to recover the physical properties of the observed objects, with a secondary emphasis on…
We present a new pipeline utilizing machine learning for classifying short-duration features in raw time-ordered data (TOD) of cosmic microwave background survey observations. The pipeline, specifically designed for the Atacama Cosmology…