Related papers: X-ray Astronomical Point Sources Recognition Using…
Classifying catalog objects as stars, galaxies, or AGN is a crucial part of any statistical study of galaxies. We describe our pipeline for binary (star/galaxy) and multiclass (star/galaxy/Type I AGN/Type II AGN) classification developed…
We present two new source extraction methods, based on Bayesian model selection and using the Bayesian Information Criterion (BIC). The first is a source detection filter, able to simultaneously detect point sources and estimate the image…
To maximize the discovery potential of future synoptic surveys, especially in the field of transient science, it will be necessary to use automatic classification to identify some of the astronomical sources. The data mining technique of…
We describe an X-ray source detection method entirely based on the maximum likelihood analysis, in application to observations with the ART-XC telescope onboard the Spectrum Roentgen Gamma observatory. The method optimally combines the data…
Astronomical source deblending is the process of separating the contribution of individual stars or galaxies (sources) to an image comprised of multiple, possibly overlapping sources. Astronomical sources display a wide range of sizes and…
We apply a combination of a Genetic Algorithms (GA) and Support Vector Machines (SVM) machine learning algorithm to solve two important problems faced by the astronomical community: star/galaxy separation, and photometric redshift…
Detection of point sources in images is a fundamental operation in astrophysics, and is crucial for constraining population models of the underlying point sources or characterizing the background emission. Standard techniques fall short in…
Our goal is to characterize AGN populations by comparing their X-ray and optical classifications. We present a sample of 99 spectroscopically identified X-ray point sources in the XMM-LSS survey which are significantly detected in the…
We report on a campaign to identify the counterparts to the population of X-ray sources discovered at the centre of our Galaxy by Wang et al.(2002) using Chandra. We have used deep, near infrared images obtained on VLT/ISAAC to identify…
Extensive astronomical surveys, like those conducted with the {\em Chandra} X-ray Observatory, detect hundreds of thousands of unidentified cosmic sources. Machine learning (ML) methods offer an efficient, probabilistic approach to classify…
Context. Serendipitous X-ray surveys have proven to be an efficient way to find rare objects, for example tidal disruption events, changing-look active galactic nuclei (AGN), binary quasars, ultraluminous X-ray sources (ULXs), and…
We introduce a procedure to identify very soft X-ray sources (VSSs) in external galaxies. Our immediate goal was to formulate a systematic procedure to identify luminous supersoft X-ray sources (SSSs), so as to allow comparisons among…
We present preliminary results from our on-going study: Comparing and optimizing source detection procedures for XMM images. By constructing realistic spatial and spectral source distributions and ``observing'' these through the XMM Science…
This paper explores the application of machine learning methods for classifying astronomical sources using photometric data, including normal and emission line galaxies (ELGs; starforming, starburst, AGN, broad line), quasars, and stars. We…
We present the classification of 26 optical counterparts to X-ray sources discovered in the Galactic Bulge Survey. We use (time-resolved) photometric and spectroscopic observations to classify the X-ray sources based on their…
The nature of a substantial percentage (about one fifth) of hard X-ray sources discovered with the BAT instrument onboard the Neil Gehrels Swift Observatory (hereafter Swift) is unknown because of the lack of an identified longer-wavelength…
VLT images in $BVI$ are used to identify the optical counterparts to bright CHANDRA X-ray points sources discovered by Kraft et al. (2001, ApJ, 560, 675) in NGC5128. Of a total of 111 X-ray point sources with L_X>2*10^{36} ergs/s present in…
Identifying X-ray binary (XRB) candidates in nearby galaxies requires distinguishing them from possible contaminants including foreground stars and background active galactic nuclei. This work investigates the use of supervised machine…
We review the current status of studies of large-scale structure in the X-ray Universe. After motivating the use X-rays for cosmological purposes, we discuss the various approaches used on different angular scales including X-ray background…
X-ray imaging and spectroscopy can be used to probe the binary content of globular clusters. Binaries are thought to play a key role in the dynamical evolution of the clusters by serving as an internal source of energy which counters the…