Related papers: Supervised Ensemble Classification of Kepler Varia…
The accurate automated classification of variable stars into their respective sub-types is difficult. Machine learning based solutions often fall foul of the imbalanced learning problem, which causes poor generalisation performance in…
Quantitative morphological classification of galaxies is important for understanding the origin of type frequency and correlations with environment. But galaxy morphological classification is still mainly done visually by dedicated…
In this paper, we revisit the problem of clustering 1318 new variable stars found in the Milky way. Our recent work distinguishes these stars based on their light curves which are univariate series of brightness from the stars observed at…
Recent re-determination of stellar atmospheric parameters for a sample of stars observed during the {\it Kepler} mission allowed to enlarge the number of {\it Kepler} B-type stars. We present the detailed frequency analysis for all these…
We present the first data release of the Kepler Smear Campaign, using collateral 'smear' data obtained in the Kepler four-year mission to reconstruct light curves of 102 stars too bright to have been otherwise targeted. We describe the…
We accurately identify and classify the variability of A-F stars in the southern continuous viewing zone of the TESS satellite. The brightness limit was set to 10 mag to ensure the utmost reliability of our results and allow for…
The analysis of the light curves of 48 B-type stars observed by Kepler is presented. Among these are 15 pulsating stars, all of which show low frequencies characteristic of SPB stars. Seven of these stars also show a few weak, isolated high…
Star clusters are often hard to find, as they may lie in a dense field of background objects or, because in the case of embedded clusters, they are surrounded by a more dispersed population of young stars. This paper discusses four…
The universe is composed of galaxies that have diverse shapes. Once the structure of a galaxy is determined, it is possible to obtain important information about its formation and evolution. Morphologically classifying galaxies means…
Large-scale photometric surveys are revolutionizing astronomy by delivering unprecedented amounts of data. The rich data sets from missions such as the NASA Kepler and TESS satellites, and the upcoming ESA PLATO mission, are a treasure…
In the last couple of decades, tremendous progress has been achieved in developing robotic telescopes and, as a result, sky surveys (both terrestrial and space) have become the source of a substantial amount of new observational data. These…
In order to understand stellar evolution, it is crucial to efficiently determine stellar surface rotation periods. An efficient tool to automatically determine reliable rotation periods is needed when dealing with large samples of stellar…
We have searched the K2 campaign 0 data for lightcurve variations associated with stellar variability. The results of this search are presented as a catalogue, giving the identifiers of nearly 2500 variable stars in the dataset. We list the…
Stellar parameters for large samples of stars play a crucial role in constraining the nature of stars and stellar populations in the Galaxy. An increasing number of medium-band photometric surveys are presently used in estimating stellar…
The NASA Kepler mission -in flight since March 2009- is producing an enormous number of high-quality continuous light curves. Now, and for the first time ever, we are able to do ensemble asteroseismology, i.e., to do an asteroseismic…
Distinguishing active galaxies from star-forming galaxies is essential for understanding galaxy evolution. Diagnostic methods like the BPT (Baldwin, Phillips, and Terlevich) diagram use optical emission-line ratios to separate galaxies.…
We measure rotation periods for 12151 stars in the Kepler field, based on the photometric variability caused by stellar activity. Our analysis returns stable rotation periods over at least six out of eight quarters of Kepler data. This…
The automatic classification of X-ray detections is a necessary step in extracting astrophysical information from compiled catalogs of astrophysical sources. Classification is useful for the study of individual objects, statistics for…
In images collected by astronomical surveys, stars and galaxies often overlap visually. Deblending is the task of distinguishing and characterizing individual light sources in survey images. We propose StarNet, a Bayesian method to deblend…
Stellar multiplicity is an ubiquitous outcome of the star formation process. Characterizing the frequency and main characteristics of multiple systems and their dependencies on primary mass and environment is therefore a powerful tool to…