BAYESIAN ANALYSIS OF COSMIC RAY PROPAGATION: EVIDENCE AGAINST HOMOGENEOUS DIFFUSION
| Autor: | Aaron C. Vincent, T. A. Porter, Michael P. Hobson, Gudlaugur Johannesson, Elena Orlando, Roberto Ruiz de Austri, Igor V. Moskalenko, Roberto Trotta, Farhan Feroz, P. B. Graff, Andrew W. Strong |
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| Přispěvatelé: | Johannesson, G, de Austri, Rr, Vincent, Ac, Moskalenko, Iv, Orlando, E, Porter, Ta, Strong, Aw, Trotta, R, Feroz, F, Graff, P, Hobson, Mp, Science and Technology Facilities Council (STFC), Science and Technology Facilities Council [2006-2012], Science and Technology Facilities Council |
| Rok vydání: | 2021 |
| Předmět: |
astroparticle physics
cosmic rays diffusion Galaxy: general ISM: general methods: statistical Parameter space 01 natural sciences Diffusion (business) 010303 astronomy & astrophysics cosmic ray Physics High Energy Astrophysical Phenomena (astro-ph.HE) astro-ph.HE 0306 Physical Chemistry (incl. Structural) SUPERNOVA-REMNANTS general [ISM] SECONDARY ELEMENTAL COMPOSITION astroparticle physic Physical Sciences 0202 Atomic Molecular Nuclear Particle and Plasma Physics Astrophysics - High Energy Astrophysical Phenomena Bar (music) astro-ph.GA Bayesian probability statistical [methods] FOS: Physical sciences Cosmic ray FERMI-LAT OBSERVATIONS Astronomy & Astrophysics Article Settore FIS/05 - Astronomia e Astrofisica 0103 physical sciences 0201 Astronomical and Space Sciences Calibration ENERGY-SPECTRA Nested sampling algorithm general [Galaxy] Science & Technology NUCLEI 010308 nuclear & particles physics CONSTRAINTS Astronomy and Astrophysics Astrophysics - Astrophysics of Galaxies Computational physics Interstellar medium MODEL Space and Planetary Science Astrophysics of Galaxies (astro-ph.GA) SOLAR MODULATION EMISSION |
| Zdroj: | Astrophys J Astrophysical journal, 2016, Vol.824(1), pp.16 [Peer Reviewed Journal] |
| ISSN: | 0004-637X |
| Popis: | We present the results of the most complete ever 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 such study to separate out low-mass isotopes ($p$, $\bar p$ and He) from the usual light elements (Be, B, C, N, O). We find that the propagation parameters that best fit $p$, $\bar p$, He data are significantly different from those that fit light elements, including the B/C and $^{10}$Be/$^9$Be secondary-to-primary ratios normally used to calibrate propagation parameters. This suggests 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. Comment: 20 pages, 10 figures, 5 tables. v2 accepted for publication in ApJ |
| Databáze: | OpenAIRE |
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