Research in many areas of modern physics such as, e.g., indirect searches for dark matter and particle acceleration in supernova remnant shocks rely heavily on studies of cosmic rays (CRs) and associated diffuse emissions (radio, microwave, X-rays, γ-rays). The numerical Galactic CR propagation code GALPROP has been shown to reproduce simultaneously observational data of many kinds related to CR origin and propagation. We report on the latest updates of GALPROP, development of WebRun, a service to the scientific community enabling easy use of the GALPROP code via web browsers, and a library of evaluated isotopic production cross sections. We also report the results of a full Bayesian analysis of propagation parameters using nested sampling and Markov Chain Monte Carlo methods (implemented in the SuperBayeS code).
GALPROP code for galactic cosmic ray propagation and associated photon emissions / Moskalenko, I. V.; Digel, S.; Johannesson, G.; Orlando, E.; Porter, T. A.; Ruiz De Austri, R.; Strong, A. W.; Trotta, R.; Vladimirov, A. E.. - 6:(2011), pp. 279-282. (Intervento presentato al convegno 32nd International Cosmic Ray Conference, ICRC 2011 tenutosi a Beijing, chn nel 2011) [10.7529/ICRC2011/V06/1194].
GALPROP code for galactic cosmic ray propagation and associated photon emissions
Trotta, R.;
2011-01-01
Abstract
Research in many areas of modern physics such as, e.g., indirect searches for dark matter and particle acceleration in supernova remnant shocks rely heavily on studies of cosmic rays (CRs) and associated diffuse emissions (radio, microwave, X-rays, γ-rays). The numerical Galactic CR propagation code GALPROP has been shown to reproduce simultaneously observational data of many kinds related to CR origin and propagation. We report on the latest updates of GALPROP, development of WebRun, a service to the scientific community enabling easy use of the GALPROP code via web browsers, and a library of evaluated isotopic production cross sections. We also report the results of a full Bayesian analysis of propagation parameters using nested sampling and Markov Chain Monte Carlo methods (implemented in the SuperBayeS code).File | Dimensione | Formato | |
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