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Proceedings Paper

Recognition of Compton scattering patterns in advanced Compton telescopes
Author(s): Andreas Zoglauer; Steven E. Boggs; Robert Andritschke; Gottfried Kanbach
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Paper Abstract

The next generation of Compton telescopes (such as MEGA or NCT) will detect impinging gamma rays by measuring one or more Compton interactions, possibly electron tracks, and a final photo absorption. However, the recovery of the original parameters of the photon, especially its energy and direction, is a challenging task, since the measured data only consists of a set of energy and position measurements and their ordering, i.e. the path of the photon, is unknown. Thus the main tasks of the pattern recognition algorithm are to identify the interaction sequence of the photon (i.e. which hit is the start point) and distinguish the pattern from background signatures, especially incompletely absorbed events. The most promising approach up to now is based on Bayesian statistics: The Compton interactions are parameterized in a multi-dimensional data space, which contains the interaction information of the Compton sequence as well as geometry information of the detector. For each data space cell the probability that the corresponding interaction sequence is one of a correctly ordered, completely absorbed source photon can be determined by Bayesian statistics and detailed simulations. This probability can then be used to distinguish source photons from incompletely absorbed photons. Simulations show that the Bayesian approach can improve the 68% event containment of the ARM distribution by up to 40%, and results in a much better separation between "good" and "bad" events. In addition, sensitivity improvements up to a factor 1.7 can be achieved.

Paper Details

Date Published: 17 September 2007
PDF: 12 pages
Proc. SPIE 6700, Mathematics of Data/Image Pattern Recognition, Compression, Coding, and Encryption X, with Applications, 67000I (17 September 2007); doi: 10.1117/12.738990
Show Author Affiliations
Andreas Zoglauer, Univ. of California, Berkeley (United States)
Steven E. Boggs, Univ. of California, Berkeley (United States)
Robert Andritschke, Max-Planck-Institut Halbleiterlabor (Germany)
Max-Planck-Institut für extraterrestrische Physik (Germany)
Gottfried Kanbach, Max-Planck-Institut für extraterrestrische Physik (Germany)

Published in SPIE Proceedings Vol. 6700:
Mathematics of Data/Image Pattern Recognition, Compression, Coding, and Encryption X, with Applications
Gerhard X. Ritter; Mark S. Schmalz; Junior Barrera; Jaakko T. Astola, Editor(s)

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