کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
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1780776 | 1523858 | 2014 | 6 صفحه PDF | دانلود رایگان |
The field of astroparticle physics is currently the focus of prolific scientific activity. In the last decade, this field has undergone significant developments thanks to several experimental results from CREAM, PAMELA, Fermi, and H.E.S.S. Moreover, the next generation of instruments, such as AMS-02 (launched on 16 May 2011) and CTA, will undoubtedly facilitate more sensitive and precise measurements of the cosmic-ray and γγ-ray fluxes. To fully exploit the wealth of high precision data generated by these experiments, robust and efficient statistical tools such as Markov Chain Monte Carlo algorithms or evolutionary algorithms, able to handle the complexity of joint parameter spaces and datasets, are necessary for a phenomenological interpretation. The Grenoble Analysis Toolkit (GreAT) is an user-friendly and modular object orientated framework in C++, which samples the user-defined parameter space with a pre- or user-defined algorithm. The functionality of GreAT is presented in the context of cosmic-ray physics, where the boron-to-carbon (B/C) ratio is used to constrain cosmic-ray propagation models.
Journal: Physics of the Dark Universe - Volumes 5–6, December 2014, Pages 29–34