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| List-Mode Likelihood Imaging Applied to COMPTEL Data |
| Category:
05. Data Analysis and Modeling Techniques |
Andreas C. Zoglauer1, S. E. Boggs2, W. Collmar3, M. Kippen4, E. Novikova5, G. Weidenspointner3, C. B. Wunderer1
1UC, Berkeley, 2University of California at Berkeley, 3Max-Planck-Institut fuer extraterrestrische Physik, Germany, 4Los Alamos National Laboratory, 5Naval Research Laboratory. |
| Presentation Number: 04.04 |
Eight years after de-orbiting CGRO, COMPTEL's 1-30 MeV all-sky imaging performance, as well as its sensitivity for continuum sources, remain unsurpassed. Moreover, currently no official successor mission exists
that might challenge COMPTEL's performance --- only GLAST is expected to improve upon COMPTEL above ~20 MeV. Since the time when the original COMPTEL data analysis techniques were developed in the 1990's, the performance of state-of-the-art computers has increased by more than a factor of 100, allowing for new analysis techniques that were unthinkable at that time. These encompass detailed orbital background simulations including detector activation, Bayesian event selection techniques, and list-mode imaging.
In this work we concentrate on the list-mode maximum likelihood expectation maximization (ML-EM) imaging method. It allows all measured information to be included into the imaging response of the instrument. As a consequence, this approach has the capability to produce improved images compared to those from the original techniques applied to COMPTEL data. We are currently in the process of adapting the list-mode approach to COMPTEL, determining the imaging response via simulations, and reanalyzing data with the ML-EM method.
We will show first results of the Galactic anti-center region, and compare them to previous COMPTEL results. |
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