The rigidity dependence of galactic cosmic-ray fluxes and its connection with the diffusion coefficient

Thanks to tremendous experimental efforts, galactic cosmic-ray fluxes are being measured up to the unprecedented per cent precision level. The logarithmic slope of these fluxes is a crucial quantity that promises us information on the diffusion properties and the primary or secondary nature of the different species. However, these measured slopes are sometimes interpreted in the pure diffusive regime, guiding to misleading conclusions. In this paper, we have studied the propagation of galactic cosmic rays by computing the fluxes of species between H and Fe using the USINE code and considering all the relevant physical processes and an updated set of cross-section data. We show that the slope of the well-studied secondary-to-primary B/C ratio is distinctly different from the diffusion coefficient slope, by an offset of about 0.2 in the rigidity range in which the AMS-02 data reach their best precision (several tens of GV). Furthermore, we have demonstrated that none of the species from H to Fe follows the expectations of the pure-diffusive regime. We argue that these differences arise from propagation processes such as fragmentation, convection, and reacceleration, which cannot be neglected. On this basis, we also provide predictions for the spectral slope of elemental fluxes not yet analysed by the AMS collaboration

Combined analysis of AMS-02 secondary-to-primary ratios: Universality of cosmic-ray propagation and consistency of nuclear cross sections

The AMS-02 collaboration released several secondary-to-primary ratios of unprecedented accuracy. These ratios can be used to test the universality of propagation for different species, and also to test the presence of breaks in the diffusion coefficient. It was shown in Weinrich et al. (A&A 639, 131, 2020) that the combined analysis of Li/C, Be/C, and B/C strengthens the case for a low-rigidity diffusion break. It was also shown that a standard propagation model successfully reproduces these ratios (and also AMS-02 N/O and 3He/4He data), without the need for additional sources of Li, Be, or B. However, significant modifications (~5-15% ) of the production cross sections are required, though these modifications remain within estimated nuclear uncertainties. We also extend our analyses to the recently published F/Si ratio and discuss how much F at the source can be accommodated by the data

An alternative classification to mixture modeling for longitudinal counts or binary measures

Classifying patients according to longitudinal measures, or trajectory classification, has become frequent in clinical research. The k-means algorithm is increasingly used for this task in case of continuous variables with standard deviations that do not depend on the mean. One feature of count and binary data modeled by Poisson or logistic regression is that the variance depends on the mean; hence, the within-group variability changes from one group to another depending on the mean trajectory level. Mixture modeling could be used here for classification though its main purpose is to model the data. The results obtained may change according to the main objective. This article presents an extension of the k-means algorithm that takes into account the features of count and binary data by using the deviance as distance metric. This approach is justified by its analogy with the classification likelihood. Two applications are presented with binary and count data to show the differences between the classifications obtained with the usual Euclidean distance versus the deviance distance