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Register a new userConstraints on cosmic-ray propagation models from a global Bayesian analysis
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Research in many areas of modern physics such as, e.g., indirect searches for dark matter and particle acceleration in SNR shocks, rely heavily on studies of cosmic rays (CRs) and associated diffuse emissions (radio, microwave, X-rays, gamma rays). While very detailed numerical models of CR propagation exist, a quantitative statistical analysis of such models has been so far hampered by the large computational effort that those models require. Although statistical analyses have been carried out before using semi-analytical models (where the computation is much faster), the evaluation of the results obtained from such models is difficult, as they necessarily suffer from many simplifying assumptions, The main objective of this paper is to present a working method for a full Bayesian parameter estimation for a numerical CR propagation model. For this study, we use the GALPROP code, the most advanced of its kind, that uses astrophysical information, nuclear and particle data as input to self-consistently predict CRs, gamma rays, synchrotron and other observables. We demonstrate that a full Bayesian analysis is possible using nested sampling and Markov Chain Monte Carlo methods (implemented in the SuperBayeS code) despite the heavy computational demands of a numerical propagation code. The best-fit values of parameters found in this analysis are in agreement with previous, significantly simpler, studies also based on GALPROP.
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The energy spectra of primary and secondary cosmic rays (CR) generally harden at several hundreds of GeV, which can be naturally interpreted by propagation effects. We adopt a spatially dependent CR propagation model to fit the spectral hardening, where a slow-diffusion disk (SDD) is assumed near the Galactic plane. We aim to constrain the propagation parameters with the Bayesian parameter estimation based on a Markov chain Monte Carlo sampling algorithm. The latest precise measurements of carbon spectrum and B/C ratio are adopted in the Bayesian analysis. The $rm{^{10}Be/^{9}Be}$ and Be/B ratios are also included to break parameter degeneracies. The fitting result shows that all the parameters are well constrained. Especially, the thickness of the SDD is limited to 0.4-0.5 kpc above and below the Galactic plane, which could be the best constraint for the slow-diffusion region among similar works. The $bar{p}/p$ ratio and amplitude of CR anisotropy predicted by the SDD model are consistent with the observations, while the predicted high-energy electron and positron fluxes are slightly and significantly lower than the observations, respectively, indicating the necessity of extra sources.
I present the first public releases (v3.4 and v3.5) of the USINE code for cosmic-ray propagation in the Galaxy (https://lpsc.in2p3.fr/usine). It contains several semi-analytical propagation models previously used in the literature (leaky-box model, 2-zone 1D and 2D diffusion models) for the calculation of nuclei ($Z=1-30$), anti-protons, and anti-deuterons. For minimisations, the geometry, transport, and source parameters of all models can be enabled as free parameters, whereas nuisance parameters are enabled on solar modulation levels, cross sections (inelastic and production), and systematics of the CR data. With a single ASCII initialisation file to configure runs, its many displays, and the speed associated to semi-analytical approaches, USINE should be a useful tool for beginners, but also for experts to perform statistical analyses of high-precision cosmic-ray data.
Multiwavelength observations suggest that clusters are reservoirs of vast amounts relativistic electrons and positrons that are either injected into and accelerated directly in the intra-cluster medium, or produced as secondary pairs by cosmic ray ions scattering on ambient protons. In these possible scenarios gamma rays are produced either through electrons upscattering low-energy photons or by decay of neutral pions produced by hadronic interactions. In addition, the high mass-to-light ratios in clusters in combination with considerable Dark Matter (DM) overdensities makes them interesting targets for indirect DM searches with gamma rays. The resulting signals are different from known point sources or from diffuse emission and could possibly be detected with the Fermi-LAT. Both WIMP annihilation/decay spectra and cosmic ray induced emission are determined by universal parameters, which make a combined statistical likelihood analysis feasible. We present initial results of this analysis leading to limits on the DM annihilation cross section or decay time and on the hadron injection efficiency.
The Picard code for the numerical solution of the Galactic cosmic ray propagation problem allows for high-resolution models that acknowledge the 3D structure of our Galaxy. Picard was used to determine diffuse gamma-ray emission of the Galaxy over the energy range from 100 MeV to 100 TeV. We discuss the impact of a cosmic-ray source distribution aligned with the Galactic spiral arms for a range of such spiral-arm models. As expected, the impact on the gamma-ray emission is most distinct in the inverse-Compton channel, where imprints of the spiral arms are visible and yield predictions that are no longer symmetric to the rotational axis of the Milkyway. We will illustrate these differences by a direct comparison to results from previous axially symmetric Galactic propagation models: we find differences in the gamma-ray flux both on global scales and on local scales related to the spiral arm tangents. We compare gamma-ray flux and spectra at on-arm vs. off-arm projections and characterize the differences to axially symmetric models.
Dwarf galaxies represent a powerful probe of annihilating dark matter particle models, with gamma-ray data setting some of the best bounds available. A major issue in improving over existing constraints consists in the limited knowledge of the astrophysical background (mostly diffuse photons, but also unresolved sources). Perhaps more worrisome, several approaches in the literature suffer of the difficulty of assessing the systematic error due to background mis-modelling. Here we propose a data-driven method to estimate the background at the dwarf position and its uncertainty, relying on an appropriate use of the whole-sky data, via an optimisation procedure of the interpolation weights. While this article is mostly methodologically oriented, we also report the bounds based on latest Fermi-LAT data and updated information for J-factors for both isolated and stacked dwarfs. Our results are very competitive with the Fermi-LAT ones, while being derived with a more general and flexible method. We discuss the impact of profiling over the J-factor as well as over the background probability distribution function, with the latter resulting for instance crucial in drawing conclusions of compatibility with DM interpretations of the so-called Galactic Centre Excess.
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