Bayesian analysis of spatial-dependent cosmic-ray propagation: astrophysical background of antiprotons and positrons

TL;DR

This paper presents a Bayesian analysis of cosmic-ray propagation using a two-halo model, providing improved predictions for secondary antiproton spectra that align with recent AMS-02 measurements, and highlights the need for additional sources to explain positron excess.

Contribution

The study introduces a two-halo propagation model with a Bayesian framework, refining cosmic-ray diffusion parameters and secondary antiproton production estimates.

Findings

Vertical extent of diffusion region ~900 pc

Diffusion coefficient scales as E^{0.15}

Antiproton data consistent with secondary production

Abstract

The AMS-02 experiment has reported a new measurement of the antiproton/proton ratio in Galactic cosmic rays (CRs). In the energy range $E\sim\,$60-450 GeV, this ratio is found to be remarkably constant. Using recent data on CR proton, helium, and carbon fluxes, 10Be/9Be and B/C ratios, we have performed a global Bayesian analysis based on a Markov-Chain Monte-Carlo sampling algorithm under a "two halo model" of CR propagation. In this model, CRs are allowed to experience a different type of diffusion when they propagate in the region close of the Galactic disk. We found that the vertical extent of this region is about 900 pc above and below the disk, and the corresponding diffusion coefficient scales with energy as $D\sim\,E^{0.15}$, describing well the observations on primary CR spectra, secondary/primary ratios and anisotropy. Under this model we have carried out improved calculations of antiparticle spectra arising from secondary CR production and their corresponding uncertainties. We made use of Monte-Carlo generators and accelerator data to assess the antiproton production cross-sections and their uncertainties. While the positron excess requires the contribution of additional unknown sources, we found that the new AMS-02 antiproton data are consistent, within the estimated uncertainties, with our calculations based on secondary production.