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The XMM-Newton serendipitous survey. VII. The third XMM-Newton serendipitous source catalogue

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 نشر من قبل Natalie Webb
 تاريخ النشر 2015
  مجال البحث فيزياء
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Thanks to the large collecting area (3 x ~1500 cm$^2$ at 1.5 keV) and wide field of view (30 across in full field mode) of the X-ray cameras on board the European Space Agency X-ray observatory XMM-Newton, each individual pointing can result in the detection of hundreds of X-ray sources, most of which are newly discovered. Recently, many improvements in the XMM-Newton data reduction algorithms have been made. These include enhanced source characterisation and reduced spurious source detections, refined astrometric precision, greater net sensitivity and the extraction of spectra and time series for fainter sources, with better signal-to-noise. Further, almost 50% more observations are in the public domain compared to 2XMMi-DR3, allowing the XMM-Newton Survey Science Centre (XMM-SSC) to produce a much larger and better quality X-ray source catalogue. The XMM-SSC has developed a pipeline to reduce the XMM-Newton data automatically and using improved calibration a new catalogue version has been produced from XMM-Newton data made public by 2013 Dec. 31 (13 years of data). Manual screening ensures the highest data quality. This catalogue is known as 3XMM. In the latest release, 3XMM-DR5, there are 565962 X-ray detections comprising 396910 unique X-ray sources. For the 133000 brightest sources, spectra and lightcurves are provided. For all detections, the positions on the sky, a measure of the quality of the detection, and an evaluation of the X-ray variability is provided, along with the fluxes and count rates in 7 X-ray energy bands, the total 0.2-12 keV band counts, and four hardness ratios. To identify the detections, a cross correlation with 228 catalogues is also provided for each X-ray detection. 3XMM-DR5 is the largest X-ray source catalogue ever produced. Thanks to the large array of data products, it is an excellent resource in which to find new and extreme objects.



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