2012/05/22 by Juan Wu, Wu, Juan
Earth and Planetary Sciences · Physics and Astronomy · #Astrophysics of Galaxies (astro-ph.GA) #Atmospheric Ozone and Climate #Dark Matter and Cosmic Phenomena #FOS: Physical sciences #High Energy Astrophysical Phenomena (astro-ph.HE) #High Energy Physics - Experiment (hep-ex) #High Energy Physics - Phenomenology (hep-ph) #Solar and Space Plasma Dynamics #astro-ph.GA #astro-ph.HE #hep-ex #hep-ph
paper · pdf · doi:10.48550/arxiv.1205.5007
Doctoral Thesis in Physics, Royal Institute of Technology (KTH), defense on 1st June 2012
arxiv created 2012/05/22 · openalex publication_date 2012/05/22 · arxiv updated 2012/05/23 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Studying the acceleration and propagation mechanisms of Galactic cosmic rays can provide information regarding astrophysical sources, the properties of our Galaxy, and possible exotic sources such as dark matter. To understand cosmic ray acceleration and propagation mechanisms, accurate measurements of different cosmic ray elements over a wide energy range are needed. The PAMELA experiment is a satellite-borne apparatus which allows different cosmic ray species to be identified over background. Measurements of the cosmic ray antiproton flux and the antiproton-to-proton flux ratio from 1.5 GeV to 180 GeV are presented in this thesis. Compared to previous experiments, PAMELA extends the energy range of antiproton measurements and provides significantly higher statistics. The derived antiproton flux and antiproton-to-proton flux ratio are consistent with previous measurements and generally considered to be produced as secondary products when cosmic ray protons and helium nuclei interact with the interstellar medium. To constrain cosmic ray acceleration and propagation models, the antiproton data measured by PAMELA were further used together with the proton spectrum reported by PAMELA, as well as the B/C data provided by other experiments. Statistical tools were interfaced with the cosmic ray propagation package GALPROP to perform the constraining analyses. Diffusion models with a linear diffusion coefficient and modified diffusion models with a low energy dependence of the diffusion coefficient were studied in the χ2 study. Uncertainties on the parameters and the goodness of fit of each model were given. Some models are further studied using the Bayesian inference. Posterior means and errors of the parameters base on our prior knowledge on them were obtained in the Bayesian framework. This method also allowed us to understand the correlation between parameters and compare models.