Related papers: Machine Learning based search for Cataclysmic Vari…

Context. Gaia has been in operations since 2014. The third Gaia data release expands from the early data release (EDR3) in 2020 by providing 34 months of multi-epoch observations that allowed us to probe, characterise and classify…

The observation of Very High Energy gamma rays (VHE, E > 100 GeV) led us to the identification of extremely energetic processes and particle acceleration sites both within our Galaxy and beyond. We expect that VHE facilities, like CTA, will…

The Zwicky Transient Facility (ZTF) was expected to detect more than one strong gravitationally-lensed supernova (glSN) per year, but only one event was identified in the first four years of the survey. This work investigates selection…

Time-varying phenomena are one of the most substantial sources of astrophysical information and their study has led to many fundamental discoveries in modern astronomy. We have developed an automated tool to search and analyze variable…

We use an independent new sample of cataclysmic variables (CVs), constructed by selecting objects for Halpha emission, to constrain the properties of the intrinsic CV population. This sample is restricted to systems that are likely to be…

We have discovered a new high proper motion cataclysmic variable (CV) in the SUPERBLINK proper motion survey, which is sensitive to stars with proper motions greater than 40 mas/yr. This CV was selected for follow-up observations as part of…

Large time-domain sky surveys generate extensive multi-year catalogs of light curves in which scientifically valuable transients, such as supernovae (SNe), are vastly outnumbered by artifacts and routine star variability. While supervised…

(Abridged) Using the Zwicky Transient Facility alert stream, we are conducting a large campaign to spectroscopically classify all transients occurring in galaxies in the Census of the Local Universe (CLU) catalog. The aim of the experiment…

A key science goal of large sky surveys such as those conducted by the Vera C. Rubin Observatory and precursors to the Square Kilometre Array is the identification of variable and transient objects. One approach is the statistical analysis…

We investigate the capabilities of the ESA Gaia mission for detecting and character- izing short timescale variability, from tens of seconds to a dozen hours. We assess the efficiency of the variogram analysis, for both detecting short…

Gaia Data Release 3 (DR3) published for the first time epoch photometry, BP/RP (XP) low-resolution mean spectra, and supervised classification results for millions of variable sources. This extensive dataset offers a unique opportunity to…

Ongoing large-scale optical time-domain surveys, such as the Zwicky Transient Facility (ZTF), are producing alerts at unprecedented rates. Analysis of transient sources has so far followed two distinct paths: archival analysis of data on…

Globular clusters (GCs) have been at the heart of many longstanding questions in many sub-fields of astronomy and, as such, systematic identification of GCs in external galaxies has immense impacts. In this study, we take advantage of M87's…

Gaia mission will offer an exceptional opportunity to perform variability studies. The data homogeneity, its optimised photometric systems, composed of 11 medium and 4-5 broad bands, the high photometric precision in G band of one milli-mag…

Machine-learning (ML) algorithms will play a crucial role in studying the large datasets delivered by new facilities over the next decade and beyond. Here, we investigate the capabilities and limits of such methods in finding galaxies with…

The recent advances in Gravitational-wave astronomy have greatly accelerated the study of Multimessenger astrophysics. There is a need for the development of fast and efficient algorithms to detect non-astrophysical transients and noises…

This is a follow-up sensitivity study on r-mode gravitational wave signals from newborn neutron stars illustrating the applicability of machine learning algorithms for the detection of long-lived gravitational-wave transients. In this…

We present a convolutional neural network to classify distinct cosmological scenarios based on the statistically similar weak-lensing maps they generate. Modified gravity (MG) models that include massive neutrinos can mimic the standard…

Fermi Gamma-ray Space Telescope has detected a diverse range of gamma-ray transients since its launch in 2008. Over the years, Fermi has accumulated an extensive public archive of transient events. Traditional classification methods for…

Efficient automated detection of flux-transient, reoccurring flux-variable, and moving objects is increasingly important for large-scale astronomical surveys. We present braai, a convolutional-neural-network, deep-learning real/bogus…