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We evaluate the effectiveness of deep learning (DL) models for reconstructing the masses of galaxy clusters using X-ray photometry data from next-generation surveys. We establish these constraints using a catalogue of realistic mock eROSITA…
We present the XXL Survey, the largest XMM programme totaling some 6.9 Ms to date and involving an international consortium of roughly 100 members. The XXL Survey covers two extragalactic areas of 25 deg2 each at a point-source sensitivity…
The study of machine learning (ML) techniques for the autonomous classification of astrophysical sources is of great interest, and we explore its applications in the context of a multifrequency data-frame. We test the use of supervised ML…
We present the XMM-LSS cluster catalogue corresponding to the CFHTLS D1 area. The list contains 13 spectroscopically confirmed, X-ray selected galaxy clusters over 0.8 deg2 to a redshift of unity and so constitutes the highest density…
We present morphological classifications obtained using machine learning for objects in SDSS DR6 that have been classified by Galaxy Zoo into three classes, namely early types, spirals and point sources/artifacts. An artificial neural…
Finding and classifying astronomical sources is key in the scientific exploitation of radio surveys. Source-finding usually involves identifying the parts of an image belonging to an astronomical source, against some estimated background.…
We analyze 18 sources that were found to show interesting properties of periodicity, very soft spectra and/or large long-term variability in X-rays in our project of classification of sources from the 2XMMi-DR3 catalog but were poorly…
Lung cancer is a major issue in worldwide public health, requiring early diagnosis using stable techniques. This work begins a thorough investigation of the use of machine learning (ML) methods for precise classification of lung cancer…
Using archival X-ray data from the second XMM-Newton serendipitous source catalogue, we present comparative analysis of the overall population of X-ray sources in the Large and Small Magellanic Clouds. We see a difference between the…
The Legacy Survey of Space and Time, to be conducted with the Vera C. Rubin Observatory, is poised to revolutionize our understanding of the Solar System by providing an unprecedented wealth of data on various objects, including the elusive…
Early X-ray surveys of the Magellanic Clouds (MCs) were performed with the imaging instruments of the Einstein, ASCA and ROSAT satellites revealing discrete X-ray sources and large-scale diffuse emission. Large samples of supernova…
Aims. M 31 has been completely imaged for the first time obtaining a luminosity lower limit ~10^35 erg s-1 in the 0.2-4.5 keV band. Our XMM-Newton EPIC survey combines archival observations with observations taken between June 2006 and…
A novel application of machine-learning (ML) based image processing algorithms is proposed to analyze an all-sky map (ASM) obtained using the Fermi Gamma-ray Space Telescope. An attempt was made to simulate a one-year ASM from a…
Galaxy cluster cosmology relies on complete and pure samples spanning a large range of masses and redshifts. In Xu et al. (2018) and Xu et al. (2022), we discovered an apparently new population of galaxy groups and clusters with, on…
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 the data analysis and the X-ray source counts for the first season of XMM-Newton observations in the COSMOS field. The survey covers ~2 deg^2 within the region of sky bounded by 9^h57.5^m<R.A.<10^h03.5^m; 1^d27.5^m<DEC<2^d57.5^m…
We present highlights from a study of a sample of 10 extreme-luminosity candidate ultraluminous X-ray sources (L_X > 5 x 10^(40) erg sec^(-1)), all at distances < 100 Mpc, identified from a cross-correlation of the RC3 catalogue of galaxies…
Modern astronomical surveys are producing datasets of unprecedented size and richness, increasing the potential for high-impact scientific discovery. This possibility, coupled with the challenge of exploring a large number of sources, has…
Local-Group galaxies provide access to samples of X-ray source populations of whole galaxies. The XMM-Newton survey of the Small Magellanic Cloud (SMC) completely covers the bar and eastern wing with a 5.6 deg^2 area in the (0.2-12.0) keV…
The morphology of radio galaxies is indicative of their interaction with their surroundings, among other effects. Since modern radio surveys contain a large number of radio sources that would be impossible to analyse and classify manually,…