Related papers: Exploring X-ray variability with unsupervised mach…
Aims: Pointed observations with XMM-Newton provide the basis for creating catalogues of X-ray sources detected serendipitously in each field. This paper describes the creation and characteristics of the 2XMM catalogue. Methods: The 2XMM…
During the last ten years, a considerable amount of effort has been made to develop algorithms for automatic classification of variable stars. That has been primarily achieved by applying machine learning methods to photometric datasets…
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…
We present an automatic, fast, accurate and robust method of classifying astronomical objects. The Self Organizing Map (SOM) as an unsupervised Artificial Neural Network (ANN) algorithm is used for classification of stellar spectra of…
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…
We show unsupervised machine learning techniques are a valuable tool for both visualizing and computationally accelerating the estimation of galaxy physical properties from photometric data. As a proof of concept, we use self organizing…
We are entering an era of unprecedented quantities of data from current and planned survey telescopes. To maximise the potential of such surveys, automated data analysis techniques are required. Here we implement a new methodology for…
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 present an unsupervised machine learning approach that can be employed for estimating photometric redshifts. The proposed method is based on a vector quantization approach called Self--Organizing Mapping (SOM). A variety of…
We present an alternative algorithm to global fitting procedures to construct Parton Distribution Functions (PDFs) parametrizations. The proposed algorithm uses Self-Organizing Maps (SOMs) which at variance with the standard Neural…
We have attempted to analyse all the available data taken by XMM-Newton as it slews between targets. This slew survey, the resultant source catalogue and the analysis procedures used are described in an accompanying paper. In this letter we…
The success of automatic classification of variable stars strongly depends on the lightcurve representation. Usually, lightcurves are represented as a vector of many statistical descriptors designed by astronomers called features. These…
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 XMM-Newton observatory has accumulated a vast archive of over 17,000 X-ray observations over the last 25 years. However, the standard data processing pipelines may fail to detect certain types of transient X-ray sources due to their…
We present a series of X-ray variability results from a long XMM-Newton + NuSTAR campaign on the bright, variable AGN NGC 3227. We present an analysis of the lightcurves, showing that the source displays typically softer-when-brighter…
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…
We directly compare X-ray and optical techniques of cluster detection by combining SDSS photometric data with a wide-field ($\sim 1.8$ deg$^{2}$) XMM-{\em Newton} survey in the North Galactic Pole region. The optical cluster detection…
With the goal of extracting as much information as possible from Chandra and XMM-Newton observations of faint, diffuse sources such as galaxy clusters, as well as those of future X-ray telescopes, we present a strategy for forward modeling…
Identification of anomalous light curves within time-domain surveys is often challenging. In addition, with the growing number of wide-field surveys and the volume of data produced exceeding astronomers ability for manual evaluation,…
The data collected by XMM-Newton as it slews between pointings currently cover almost half the entire sky, and many familiar features and new sources are visible. The soft-band sensitivity limit of the Slew is close to that of the RASS, and…