Related papers: Data characterization using artificial-star tests:…
With nearly two billion stars observed and their corresponding astrometric parameters evaluated in the recent Gaia mission, the number of astrometric binary candidates have risen significantly. Due to the surplus of astrometric data, the…
Coadded astronomical images are created by stacking multiple single-exposure images. Because coadded images are smaller in terms of data size than the single-exposure images they summarize, loading and processing them is less…
A flood of reliable seismic data will soon arrive. The migration to larger telescopes on the ground may free up 4-m class instruments for multi-site campaigns, and several forthcoming satellite missions promise to yield nearly uninterrupted…
In this paper, we present a deep learning system approach to estimating luminosity, effective temperature, and surface gravity of O-type stars using the optical region of the stellar spectra. In previous work, we compare a set of machine…
The strength and vertical distribution of atmospheric turbulence is a key factor determining the performance of optical and infrared telescopes, with and without adaptive optics. Yet, this remains challenging to measure. We describe a new…
Currently available star cluster catalogues from HST imaging of nearby galaxies heavily rely on visual inspection and classification of candidate clusters. The time-consuming nature of this process has limited the production of reliable…
Estimating stellar masses and radii is a challenge for most of the stars but their knowledge is critical for many different astrophysical fields. One of the most extended techniques for estimating these variables are the so-called empirical…
Since the early 1970s, stellar population modelling has been one of the basic tools for understanding the physics of unresolved systems from observation of their integrated light. Models allow us to relate the integrated spectra (or…
The growth of sky surveys and the large amount of stellar spectra in the current databases, has generated the necessity of developing new methods to estimate atmospheric parameters, a fundamental task on stellar research. In this work we…
The advent of space-based observatories such as CoRoT and Kepler has enabled the testing of our understanding of stellar evolution on thousands of stars. Evolutionary models typically require five input parameters, the mass, initial Helium…
The age of an individual star cannot be measured, only estimated through mostly model-dependent or empirical methods, and no single method works well for a broad range of stellar types or for a full range in age. This review presents a…
Astrophysics and cosmology are rich with data. The advent of wide-area digital cameras on large aperture telescopes has led to ever more ambitious surveys of the sky. Data volumes of entire surveys a decade ago can now be acquired in a…
Face clustering is a promising method for annotating unlabeled face images. Recent supervised approaches have boosted the face clustering accuracy greatly, however their performance is still far from satisfactory. These methods can be…
Variable star analysis and classification is an important task in the understanding of stellar features and processes. While historically classifications have been done manually by highly skilled experts, the recent and rapid expansion in…
We show that the errors due to atmospheric refraction are present in the magnitudes determined with the Difference Images Analysis method. In case of single, unblended stars the size of the effect agrees with the theoretical prediction. But…
It is currently impossible to determine the abundances of stellar populations star-by-star in dense stellar systems more distant than a few megaparsecs. Therefore, methods to analyse the composite light of stellar systems are required. I…
Understanding the star-formation properties of galaxies as a function of cosmic epoch is a critical exercise in studies of galaxy evolution. Traditionally, stellar population synthesis models have been used to obtain best fit parameters…
We present the first application of the novel approach based on data-driven machine learning methods applied to Multi-Unit Spectroscopic Explorer (MUSE) field data to derive stellar abundances of star clusters. MUSE has been used to target…
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…
The photometric analysis of sample Am stars is carried out to determine the stellar characteristics and to constrain the stellar dynamics. The spectroscopic analysis of the studied Am stars confirms their general characteristics of Am…