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In time-domain astronomy, STLF (Short-Timescale and Large Field-of-view) sky survey is the latest way of sky observation. Compared to traditional sky survey who can only find astronomical phenomena, STLF sky survey can even reveal how short…
The wish list of astronomers includes a tool that reveals quenching of star formation in galaxies directly as it proceeds. Here, we present a proof-of-concept for a new quenching-and-bursting diagnostic, a "change index" for star formation,…
AstronomicAL is a human-in-the-loop interactive labelling and training dashboard that allows users to create reliable datasets and robust classifiers using active learning. This technique prioritises data that offer high information gain,…
Stellar light curves contain valuable information about oscillations and granulation, offering insights into stars' internal structures and evolutionary states. Traditional asteroseismic techniques, primarily focused on power spectral…
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…
A machine-learning-based method is developed to identify objects with unusual stellar spectra. The method employs an autoencoder, a neural network trained to compress spectral data into a low-dimensional representation and subsequently…
I present a discussion of fundamental stellar parameters and their observational determination in the context of interferometric measurements with current and future optical/infrared interferometric facilities. Stellar parameters and the…
FALCON is an original concept for a next generation spectrograph at ESO VLT or at future ELTs. It is a spectrograph including multiple small integral field units (IFUs) which can be deployed within a large field of view such as that of…
A key to understand exoplanets is characterisation of their host stars. One of the most powerful tools to characterise stellar properties like effective temperature, surface gravity and metallicity, is spectroscopy based on observations of…
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…
This paper investigates the problem of prediction of stellar parameters, based on the star's electromagnetic spectrum. The knowledge of these parameters permits to infer on the evolutionary state of the star. From a statistical point of…
Doppler imaging, a technique which inverts spectral line profile variations of an Ap star into a two-dimensional abundance maps, provides new observational constraints on diffusion mechanism in the presence of a global magnetic field. A…
Background. Relative astrometry at or below the micro-arcsec level with a 1m class space telescope has been repeatedly proposed as a tool for exo-planet detection and characterization, as well as for several topics at the forefront of…
Asteroseismology has the capability of delivering stellar properties which would otherwise be inaccessible, such as radii, masses and thus ages of stars. When coupling this information with classical determinations of stellar parameters,…
One of the aims of LSST is to perform a systematic survey of star clusters and star forming regions (SFRs) in our Galaxy. In particular, the observations obtained with LSST will make a big difference in Galactic regions that have been…
Space observatories such as $\textit{Kepler}$ have provided data that can potentially revolutionise our understanding of stars. Through detailed asteroseismic analyses we are capable of determining fundamental stellar parameters and reveal…
The polarization of light is a critically under-utilized, rich source of information in astronomy. For stars in particular, surface magnetism polarization that can be detected and measured with spectro-polarimetry. Many questions about…
We have designed a powerful new algorithm to detect stellar streams in an automated and systematic way. The algorithm, which we call the STREAMFINDER, is well suited for finding dynamically cold and thin stream structures that may lie along…
Despite the great promise of machine-learning algorithms to classify and predict astrophysical parameters for the vast numbers of astrophysical sources and transients observed in large-scale surveys, the peculiarities of the training data…
The search for fast optical transients, such as the expected electromagnetic counterparts to binary neutron star mergers, is riddled with false positives ranging from asteroids to stellar flares. While moving objects are readily rejected…