期刊
ASTROPHYSICAL JOURNAL
卷 808, 期 2, 页码 -出版社
IOP PUBLISHING LTD
DOI: 10.1088/0004-637X/808/2/137
关键词
methods: statistical; techniques: image processing; X-rays: stars
资金
- Smithsonian Competitive Grants Program for Science Fund [40488100HH0043]
- CHASC International Astrostatistics Center
- NSF [DMS 1208791, DMS 1209232]
- Harvard Statistics Department
- NASA [NAS8-03060]
- Chandra grant [AR0-11001X]
- Wolfson Research Merit Award by British Royal Society
- Marie-Curie Career Integration Grant by European Commission
- STFC [ST/K001051/1] Funding Source: UKRI
- Science and Technology Facilities Council [ST/K001051/1] Funding Source: researchfish
We present a powerful new algorithm that combines both spatial information (event locations and the point-spread function) and spectral information (photon energies) to separate photons from overlapping sources. We use Bayesian statistical methods to simultaneously infer the number of overlapping sources, to probabilistically separate the photons among the sources, and to fit the parameters describing the individual sources. Using the Bayesian joint posterior distribution, we are able to coherently quantify the uncertainties associated with all these parameters. The advantages of combining spatial and spectral information are demonstrated through a simulation study. The utility of the approach is then illustrated by analysis of observations of FK Aqr and FL Aqr with the XMM-Newton Observatory and the central region of the Orion Nebula Cluster with the Chandra X-ray Observatory.
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