TY  - JOUR
AU  - Johannesson, G.
AU  - Ruiz de Austri, R.
AU  - Vincent, A. C.
AU  - Moskalenko, I. V.
AU  - Orlando, E.
AU  - Porter, T. A.
AU  - Strong, A. W.
AU  - Trotta, R.
AU  - Feroz, F.
AU  - Graff, P.
AU  - Hobson, M. P.
PY  - 2016
DA  - 2016//
TI  - Bayesian analysis of cosmic-ray propagation: evidence against homogeneous diffusion
T2  - Astrophys. J.
JO  - Astrophysical Journal
SP  - 16
EP  - 19pp
VL  - 824
IS  - 1
PB  - Iop Publishing Ltd
KW  - astroparticle physics
KW  - cosmic rays
KW  - diffusion
KW  - Galaxy: general
KW  - ISM: general
KW  - methods: statistical
AB  - We present the results of the most complete scan of the parameter space for cosmic ray (CR) injection and propagation. We perform a Bayesian search of the main GALPROP parameters, using the MultiNest nested sampling algorithm, augmented by the BAMBI neural network machine-learning package. This is the first study to separate out low-mass isotopes (p, (p) over bar and He) from the usual light elements (Be, B, C, N, and O). We find that the propagation parameters that best-fit p, (p) over bar, and He data are significantly different from those that fit light elements, including the B/C and Be-10/Be-9 secondary-to-primary ratios normally used to calibrate propagation parameters. This suggests that each set of species is probing a very different interstellar medium, and that the standard approach of calibrating propagation parameters using B/C can lead to incorrect results. We present posterior distributions and best-fit parameters for propagation of both sets of nuclei, as well as for the injection abundances of elements from H to Si. The input GALDEF files with these new parameters will be included in an upcoming public GALPROP update.
SN  - 0004-637x
UR  - http://arxiv.org/abs/1602.02243
UR  - https://doi.org/10.3847/0004-637X/824/1/16
DO  - 10.3847/0004-637X/824/1/16
LA  - English
N1  - WOS:000377937300016
ID  - Johannesson_etal2016
ER  -