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The Grenoble Analysis Toolkit (GreAT)-A statistical analysis framework
Stockholms universitet, Naturvetenskapliga fakulteten, Fysikum. Stockholms universitet, Naturvetenskapliga fakulteten, Oskar Klein-centrum för kosmopartikelfysik (OKC). Institut Polytechnique de Grenoble, France.
2014 (engelsk)Inngår i: Physics of the Dark Universe, E-ISSN 2212-6864, Vol. 5-6, s. 29-34Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

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 gamma-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.

sted, utgiver, år, opplag, sider
2014. Vol. 5-6, s. 29-34
Emneord [en]
Statistical analysis, Markov Chain Monte Carlo, Cosmic-ray physics
HSV kategori
Identifikatorer
URN: urn:nbn:se:su:diva-112910DOI: 10.1016/j.dark.2014.07.002ISI: 000346211300003OAI: oai:DiVA.org:su-112910DiVA, id: diva2:782710
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AuthorCount:2;

Tilgjengelig fra: 2015-01-22 Laget: 2015-01-19 Sist oppdatert: 2023-07-21bibliografisk kontrollert

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Totalt: 34 treff
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