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Published May 1, 2008 | Published
Journal Article Open

BAT X-Ray Survey. I. Methodology and X-Ray Identification

Abstract

We applied the maximum likelihood (ML) method, as an image reconstruction algorithm, to the BAT X-Ray Survey (BXS). This method was specifically designed to preserve the full statistical information in the data and to avoid mosaicking of many exposures with different pointing directions, thus reducing systematic errors when co-adding images. We reconstructed, in the 14–170 keV energy band, the image of a 90 x 90 deg^2 sky region, centered on (R.A., decl.)=(105°,-25°), which BAT surveyed with an exposure time of ~1 Ms (in 2005 November). The best sensitivity in our image is ~0.85 mcrab or 2.0 x 10-11 ergs cm−2. We detect 49 hard X-ray sources above the 4.5 σ level; of these, only 12 were previously known as hard X-ray sources (>15 keV). Swift XRT observations allowed us to firmly identify the counterparts for 15 objects, while 2 objects have Einstein IPC counterparts (Harris et al. 1990); in addition to those, we found a likely counterpart for 13 objects by correlating our sample with the ROSAT All-Sky Survey Bright Source Catalog (Voges et al. 1999). Seven objects remain unidentified. Analysis of the noise properties of our image shows that ~75% of the area is surveyed to a flux limit of ~1 mcrab. This study shows that the coupling of the ML method to the most sensitive, all-sky surveying, hard X-ray instrument, BAT, is able to probe for the first time the hard X-ray sky to the millicrab flux level. The successful application of this method to BAT demonstrates that it could also be applied with advantage to similar instruments such as INTEGRAL IBIS.

Additional Information

© 2008. The American Astronomical Society. Received 2007 July 18; accepted 2007 December 17. M.A. acknowledges N. Gehrels and the BAT team for the warm hospitality and enlightening discussions, A. Yoldas for all his tips and tricks about parallel programming and Python. The anonymous referee is acknowledged for his helpful comments which improved the manuscript. This research has made use of the NASA/ IPAC Extragalactic Database (NED), which is operated by the Jet Propulsion Laboratory, California Institute of Technology, of data obtained from the High Energy Astrophysics Science Archive Research Center (HEASARC) provided by NASA's Goddard Space Flight Center, of the SIMBAD Astronomical Database, which is operated by the Centre de Données astronomiques de Strasbourg, of the Sloan Digital Sky Survey (SDSS) managed by the Astrophysical Research Consortium (ARC) for the Participating Institutions, the National Aeronautics and Space Administration, the National Science Foundation, the Department of Energy, the Japanese Monbukagakusho, and the Max Planck Society, and of the ROSAT All Sky Survey maintained by the Max-Planck-Institut für extraterrestrische Physik.

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Created:
August 22, 2023
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October 17, 2023