Bibtype 
Inproceedings 
Bibkey 
Ruhe/etal/2016c 
Author 
Ruhe, T. and Börner, M. and Wornowizki, M. and Voigt, T. and Rhode, W. and Morik, K. 
Editor 
Marco Molinaro, Keith Shortridge, and Fabio Pasian 
Title 
Mining for Spectra  The {D}ortmund {S}pectrum {E}stimation {A}lgorithm 
Booktitle 
26th Astronomical Data Analysis Software and Systems conference (ADASS) 
Volume 
521 
Pages 
394 
Publisher 
Astronomical Society of the Pacific 
Abstract 
Obtaining the energy spectra of incident particles such as neutrinos or gammarays is a common challenge in neutrino and AirCherenkov astronomy. Mathematically this corresponds to an inverse problem, which is described by the Fredholm integral equation of the first kind. Several algorithms for solving inverse problems exist, which are, however, somewhat limited. This limitation arises from the limited number of input observables and the fact that information on individual events is lost and only the unfolded distribution is returned. In this paper we present the Dortmund Spectrum Estimation Algorithm (DSEA), which aims at overcoming the aforementioned obstacles by treating the inverse problem as a multinominal classification task. This modular and highly flexible algorithm can easily be tailored to a problem at hand. To avoid a potential bias on the class distribution used for the training of the learner, DSEA can be applied in an iterative manner using a uniform classdistribution as input.

Note 
Accepted for publication 
Year 
2016 
Projekt 
SFB876C3 