@Article{Johannesson_etal2016,
author="Johannesson, G.
and Ruiz de Austri, R.
and Vincent, A. C.
and Moskalenko, I. V.
and Orlando, E.
and Porter, T. A.
and Strong, A. W.
and Trotta, R.
and Feroz, F.
and Graff, P.
and Hobson, M. P.",
title="Bayesian analysis of cosmic-ray propagation: evidence against homogeneous diffusion",
journal="Astrophysical Journal",
year="2016",
publisher="Iop Publishing Ltd",
volume="824",
number="1",
pages="16--19pp",
optkeywords="astroparticle physics; cosmic rays; diffusion; Galaxy: general; ISM: general; methods: statistical",
abstract="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.",
optnote="WOS:000377937300016",
optnote="exported from refbase (https://references.ific.uv.es/refbase/show.php?record=2727), last updated on Thu, 07 Jul 2016 11:10:05 +0000",
issn="0004-637x",
doi="10.3847/0004-637X/824/1/16",
opturl="http://arxiv.org/abs/1602.02243",
opturl="https://doi.org/10.3847/0004-637X/824/1/16",
archivePrefix="arXiv",
eprint="1602.02243",
language="English"
}