Abstract
A common task in gamma-ray astronomy is to extract spectral information, such as model constraints and incident photon spectrum estimates, given the measured energy deposited in a detector and the detector response. This is the classic problem of spectral “deconvolution” or spectral inversion. The methods of forward folding (i.e., parameter fitting) and maximum entropy “deconvolution” (i.e., estimating independent input photon rates for each individual energy bin) have been used successfully for gamma-ray solar flares (e.g., Rank, 1997; Share and Murphy, 1995). These methods have worked well under certain conditions but there are situations were they don’t apply. These are: 1) when no reasonable model (e.g., fewer parameters than data bins) is yet known, for forward folding; 2) when one expects a mixture of broad and narrow features (e.g., solar flares), for the maximum entropy method; and 3) low count rates and low signal-to-noise, for both. Low count rates are a problem because these methods (as they have been implemented) assume Gaussian statistics but Poisson are applicable. Background subtraction techniques often lead to negative count rates. For Poisson data the Maximum Likelihood Estimator (MLE) with a Poisson likelihood is appropriate. Without a regularization term, trying to estimate the “true” individual input photon rates per bin can be an ill-posed problem, even without including both broad and narrow features in the spectrum (i.e., amultiscale approach). One way to implement this regularization is through the use of a suitable Bayesian prior. Nowak and Kolaczyk (1999) have developed a fast, robust, technique using a Bayesian multiscale framework that addresses these problems with added algorithmic advantages. We outline this new approach and demonstrate its use with time resolved solar flare gamma-ray spectroscopy.
Department
Space Science Center, Physics
Publication Date
2001
Journal Title
AIP Conference Proceedings
Publisher
AIP Publishing
Digital Object Identifier (DOI)
10.1063/1.1419486
Document Type
Conference Proceeding
Recommended Citation
Bayesian multiscale deconvolution applied to gamma-ray spectroscopy Young, C. A. and Connors, A. and Kolaczyk, E. and McConnell, M. and Rank, G. and Ryan, J. M. and Schönfelder, V., AIP Conference Proceedings, 587, 701-705 (2001), DOI:http://dx.doi.org/10.1063/1.1419486
Rights
© 2001 American Institute of Physics