Related papers: Stellar flare detection in XMM-Newton with gradien…

The X-ray emission of neutron stars enables a probe of their temperatures, geometries, and magnetospheric properties. The current number of X-ray emitting pulsars is insufficient to rule out observational biases that may arise from poorly…

Upcoming synoptic surveys are set to generate an unprecedented amount of data. This requires an automatic framework that can quickly and efficiently provide classification labels for several new object classification challenges. Using data…

NGC 253 is a local, star-bursting spiral galaxy with strong X-ray emission from hot gas, as well as many point sources. We have conducted a spectral survey of the X-ray population of NGC 253 using a deep XMM-Newton observation.NGC 253 only…

Identifying stars belonging to different classes is vital in order to build up statistical samples of different phases and pathways of stellar evolution. In the era of surveys covering billions of stars, an automated method of identifying…

We proposed a machine learning approach to identify and distinguish dusty stellar sources employing supervised and unsupervised methods and categorizing point sources, mainly evolved stars, using photometric and spectroscopic data collected…

Modern soft X-ray observatories can yield unique insights into time domain astrophysics, and a huge amount of information is stored - and largely unexploited - in data archives. Like a treasure-hunt, the EXTraS project harvested the…

The field of radio astronomy is witnessing a boom in the amount of data produced per day due to newly commissioned radio telescopes. One of the most crucial problems in this field is the automatic classification of extragalactic radio…

AIMS: We present the optical classification and redshift of 348 X-ray selected sources from the XMM-Newton Bright Serendipitous Survey (XBS) which contains a total of 400 objects (identification level = 87%). About 240 are new…

The CFHTLS presents a unique data set for weak lensing studies, having high quality imaging and deep multi-band photometry. We have initiated an XMM-CFHTLS project to provide X-ray observations of the brightest X-ray selected clusters…

Explainable AI (XAI) methods are frequently applied to obtain qualitative insights about deep models' predictions. However, such insights need to be interpreted by a human observer to be useful. In this paper, we aim to use explanations…

We present light curves and flares from a seven day, multi-wavelength observational campaign of AU Mic, a young and active dM1e star with exoplanets and a debris disk. We report on 73 unique flares between the X-ray to optical data. We use…

The variable stars in the VSX catalog are derived from a multitude of inhomogeneous data sources and classification tools. This inhomogeneity complicates our understanding of variable star types, statistics, and properties, and it directly…

The members of the Eta Chamaleontis cluster are in an evolutionary stage in which disks are rapidly evolving. It also presents some peculiarities, such as the large fraction of binaries and accretion disks, probably related with the cluster…

We have obtained a deep 8-field XMM-Newton mosaic of M33 covering the galaxy out to the D$_{25}$ isophote and beyond to a limiting 0.2--4.5 keV unabsorbed flux of 5$\times$10$^{-16}$ erg cm$^{-2}$ s$^{-1}$ (L${>}$4$\times$10$^{34}$ erg…

We describe the construction of a highly reliable sample of approximately 7,000 optically faint periodic variable stars with light curves obtained by the asteroid survey LINEAR across 10,000 sq.deg of northern sky. Majority of these…

We perform a survey of Oe and Be stars in the X-ray range. To this aim, we cross-correlated XMM-Newton and Chandra catalogs of X-ray sources with a list of Be stars, finding 84 matches in total. Of these, 51 objects had enough counts for a…

We present a catalog of cross-correlated radio, infrared and X-ray sources using a very restrictive selection criteria with an IDL-based code developed by us. The significance of the observed coincidences was evaluated through Monte Carlo…

In this experiment, we created a Multiple-Input Neural Network, consisting of Convolutional and Multi-layer Neural Networks. With this setup the selected highest-performing neural network was able to distinguish variable stars based on the…

By studying the variability of blazars across the electromagnetic spectrum, it is possible to resolve the underlying processes responsible for rapid flux increases, so-called flares. We report on an extremely bright X-ray flare in the…

In this paper, we explore the feasibility of using machine learning regression as a method of extracting basic stellar parameters and line-of-sight extinctions from spectro-photometric data. We built a stable gradient-boosted random-forest…