The American Astronomical Society, find out more

The American Astronomical Society, find out more

The Institute of Physics, find out more

The Institute of Physics, find out more

BAYESIAN ANALYSIS OF COSMIC RAY PROPAGATION: EVIDENCE AGAINST HOMOGENEOUS DIFFUSION

G. Jóhannesson1, R. Ruiz de Austri2, A. C. Vincent3, I. V. Moskalenko4,5
, E. Orlando4,5, T. A. Porter4,5, A. W. Strong6, R. Trotta7,8

, F. Feroz9, P. Graff10,11Show full author list

Published 2016 June 3 • © 2016. The American Astronomical Society. All rights reserved.
The Astrophysical Journal, Volume 824, Number 1 Citation G. Jóhannesson et al 2016 ApJ 824 16
Download Article PDF
Figures
Tables
References
Download PDF

1482 Total downloads
70
70 total citations on Dimensions.
Turn on MathJax

Get permission to re-use this article

Share this article

Share this content via email
Share on Facebook
Share on Twitter
Share on Google+
Share on Mendeley

Article information
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, $\bar{p}$, and He) from the usual light elements (Be, B, C, N, and O). We find that the propagation parameters that best-fit $p,\bar{p}$, and He data are significantly different from those that fit light elements, including the B/C and 10Be/9Be 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.