Related papers: An automated method to detect and characterise sem…

In the past decade, HCI surveys provided new insights about the frequency and properties of substellar companions at separation larger than 5 au. In this context, our study aims to detect and characterise potential exoplanets and brown…

Using 172 plates taken with the 40-cm astrograph of the Sternberg Astronomical Institute (Lomonosov Moscow University) in 1976-1994 and digitized with the resolution of 2400 dpi, we discovered and studied 275 new variable stars. We present…

The structural parameters, like the inclination, i and the position angle of the line of nodes (PA_lon) of the disk of the Large Magellanic Cloud (LMC) are estimated using the JH photometric data of red clump stars from the Infrared Survey…

The number of star clusters that populate the Large Magellanic Cloud (LMC) at deprojected distances < 4 deg has been recently found to be nearly double the known size of the system. Because of the unprecedented consequences of this outcome…

The Magellanic Clouds (MCs) are excellent locations to study stellar dust emission and its contribution to galaxy evolution. Through spectral and photometric classification, MCs can serve as a unique environment for studying stellar…

Flares are a well-studied aspect of the Sun's magnetic activity. Detecting and classifying solar flares can inform the analysis of contamination caused by stellar flares in exoplanet transmission spectra. In this paper, we present a…

The next generation of data-intensive surveys are bound to produce a vast amount of data, which can be dealt with using machine-learning methods to explore possible correlations within the multi-dimensional parameter space. We explore the…

We present an application of self-adaptive supervised learning classifiers derived from the Machine Learning paradigm, to the identification of candidate Globular Clusters in deep, wide-field, single band HST images. Several methods…

We analyse a catalogue of simulated clusters within the theoretical framework of the Spherical Collapse Model (SCM), and demonstrate that the relation between the infall velocity of member galaxies and the cluster matter overdensity can be…

This document presents the results from our spectroscopic survey of Halpha emitters in galactic and SMC open clusters with the ESO Wide Field Imager in its slitless spectroscopic mode. First of all, for the galactic open cluster NGC6611, in…

A survey of extended objects in the Large Magellanic Cloud was carried out on the ESO/SERC R and J Sky Survey Atlases, checking entries in previous catalogs and searching for new objects. The census provided 6659 objects including star…

The evolutionary classification of molecular clumps, crucial for understanding star formation, is commonly based on human-assigned categories derived from infrared (IR) emission and well-established morphological criteria. However, due to…

We outline here the next generation of cluster-finding algorithms. We show how advances in Computer Science and Statistics have helped develop robust, fast algorithms for finding clusters of galaxies in large multi-dimensional astronomical…

In this paper we report a clustering analysis of upper main-sequence stars in the Small Magellanic Cloud, using data from the VMC survey (the VISTA near-infrared YJKs survey of the Magellanic system). Young stellar structures are identified…

Aims. As a new approach to the study of resolved stellar populations in nearby galaxies, our goal is to demonstrate in NGC300 that integral field spectroscopy with high spatial resolution and excellent seeing conditions reaches an…

High-dimensional clustering analysis is a challenging problem in statistics and machine learning, with broad applications such as the analysis of microarray data and RNA-seq data. In this paper, we propose a new clustering procedure called…

A new approach to the study of the large-scale stellar cluster distribution in the Galaxy based on two-point correlation techniques is presented. The basic formalism for this method is outlined and its applications are then investigated by…

Machine learning techniques can reveal hidden structure in large data amounts and can potentially extent or even replace analytical scientific methods. In nanophotonics, modes can increase the light yield from emitters located inside the…

A search for $\gamma$-ray emission from SNRs in the Large Magellanic Cloud (LMC) based on the detection of concentrations in the arrival direction Fermi-LAT images of photons at energies higher than 10 GeV found significant evidence for 9…

We develop a galaxy cluster finding algorithm based on spectral clustering technique to identify optical counterparts and estimate optical redshifts for X-ray selected cluster candidates. As an application, we run our algorithm on a sample…