Disentangling Overlapping Astronomical Sources using Spatial and Spectral Information

Abstract

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.

arXiv comment34 pages, 15 figures, references added

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• Improved Point Source Detection in Crowded Fields using Probabilistic Cataloging
• Multiband Probabilistic Cataloging: A Joint Fitting Approach to Point Source Detection and Deblending
• eBASCS: Disentangling Overlapping Astronomical Sources II, using Spatial, Spectral, and Temporal Information
• PCAT-DE: Reconstructing point-like and diffuse signals in astronomical images using spatial and spectral information
• Identifying diffuse spatial structures in high-energy photon lists
• Identification of high-energy astrophysical point sources via hierarchical Bayesian nonparametric clustering