相关论文: Explainable machine learning classification of \te…

An Artificial Neural Network (ANN) has been employed using a supervised back-propagation scheme to classify 2000 bright sources from the Calgary database of IRAS (Infrared Astronomy Satellite) spectra in the wavelength region of 8-23…

In this work we revisit five different point sources within or behind galaxy clusters in order to constrain the coupling constant between axion-like particles (ALPs) and photons. We use three distinct machine learning (ML) techniques and…

We used 3.1 million spectroscopically labelled sources from the Sloan Digital Sky Survey (SDSS) to train an optimised random forest classifier using photometry from the SDSS and the Widefield Infrared Survey Explorer (WISE). We applied this…

With growing data volumes from synoptic surveys, astronomers must become more abstracted from the discovery and introspection processes. Given the scarcity of follow-up resources, there is a particularly sharp onus on the frameworks that…

We present a machine learning model to classify Active Galactic Nuclei (AGN) and galaxies (AGN-galaxy classifier) and a model to identify type 1 (optically unabsorbed) and type 2 (optically absorbed) AGN (type 1/2 classifier). We test…

Classification will be an important first step for upcoming surveys that will detect billions of new sources such as LSST and Euclid, as well as DESI, 4MOST and MOONS. The application of traditional methods of model fitting and…

Procedures based on current methods to detect sources in X-ray images are applied to simulated XMM images. All significant instrumental effects are taken into account, and two kinds of sources are considered -- unresolved sources…

We report preliminary results from an arcsecond-resolution X-ray survey of nearby galaxies using ACIS on board Chandra. The total sample consists of 41 low-luminosity AGNs, including Seyferts, LINERs, and LINER/H II transition objects. In…

We report on Chandra observations of 18 hard X-ray (>20 keV) sources discovered with the INTEGRAL satellite near the Galactic plane. For 14 of the INTEGRAL sources, we have uncovered one or two potential Chandra counterparts per source.…

In this work, Machine Learning (ML) methods are used to efficiently identify the unassociated sources and the Blazar Candidate of Uncertain types (BCUs) in the Fermi-LAT Third Source Catalog (3FGL). The aims are twofold: 1) to distinguish…

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…

The NuSTAR serendipitous survey has already uncovered a large number of Active Galactic Nuclei (AGN), providing new information about the composition of the Cosmic X-ray Background. For the AGN off the Galactic plane, it has been possible…

We present a machine-learning approach for estimating galaxy cluster masses from Chandra mock images. We utilize a Convolutional Neural Network (CNN), a deep machine learning tool commonly used in image recognition tasks. The CNN is trained…

Optical spectroscopic identification of the nature of 21 unidentified southern hard X-ray objects is reported here in the framework of our campaign aimed at determining the nature of newly-discovered and/or unidentified sources detected by…

The advanced capabilities of the Chandra and XMM-Newton observatories mean that, for the first time, the detailed study of the brightest point-like X-ray sources in nearby galaxies outside of the local group is a realistic aim. Here, we…

We present an analysis of the X-ray properties of a sample of solar- and late-type field stars identified in the Chandra Cosmic Evolution Survey (COSMOS), a deep (160ks) and wide (0.9 deg2) extragalactic survey. The sample of 60 sources was…

This study utilizes unsupervised machine learning, specifically the uniform manifold approximation and projection (UMAP) algorithm, to classify optical spectra originating from star-forming regions, Seyferts, and low-ionization (nuclear)…

The launch of the Chandra X-ray Observatory in July 1999 opened a new era in X-ray astronomy. Its unprecedented, <0.5" spatial resolution and low background are providing views of the X-ray sky 10-100 times fainter than previously possible.…

Using archival spectral-imaging data with a total exposure of $\sim144$ ks obtained by {\it Chandra}, 43 X-ray sources are detected within the half-light radius of globular cluster M62 (NGC6266). Based on the X-ray colour-luminosity diagram…

We present results of a Chandra survey of the ultra-luminous X-ray sources (ULX) in 13 normal galaxies, in which we combine source detection with X-ray flux measurement. 22 ULX were detected, i.e. with L_x > 1 x 10^{39} erg s^{-1} (L_10),…