Bayesian Multiscale Deconvolution Applied to Gamma-ray Spectroscopy

Authors

C A. Young, Goddard Space Flight CenterFollow
A Connors, University of New Hampshire - Main CampusFollow
E Kolaczyk, Boston University
Mark L. McConnell, University of New Hampshire - Main CampusFollow
G Rank, Max-Planck-Institut für extraterrestrische Physik
James M. Ryan, University of New HampshireFollow
V Schonfelder, Max-Planck-Institut für extraterrestrische PhysikFollow

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 [2]. 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. [5]). Nowak and Kolaczyk [4] have developed a fast, robust, technique using a Bayesian multiscale frame-work that addresses many problems with added algorithmic advantages. We briefly mention this new approach and demonstrate its use with time resolved solar flare gamma-ray spectroscopy.

Department

Space Science Center, Physics

Publication Date

2003

Journal Title

Third Statistical Challenges in Modern Astronomy Conference

Publisher

Springer

Digital Object Identifier (DOI)

10.1007/0-387-21529-8_67

Document Type

Book Chapter

Recommended Citation

C. A. Young, A. Connors, E. Kolaczyk, M. L. McConnell, G. Rank, J. M. Ryan, and V. Schönfelder. "Bayesian Multiscale Deconvolution Applied to Gamma-ray Spectroscopy." Feigelson, E. D., & Babu, G. J. (2003). Statistical challenges in astronomy. New York: Springer. pp 503-504. Print.

Rights

Springer-Verlag New York, Inc.