# Fitting B/C cosmic-ray data in the AMS-02 era: A cookbook

## TL;DR

This paper refines the analysis methodology for interpreting high-precision AMS-02 cosmic-ray data, addressing model accuracy, nuclear cross-section uncertainties, and error correlations to improve the reliability of propagation parameter estimates.

## Contribution

It introduces a comprehensive framework incorporating covariance matrices and nuisance parameters to mitigate biases in cosmic-ray data analysis.

## Key findings

- Mis-modeling nuclear cross-sections biases results.
- Proper error correlation treatment is crucial for accurate interpretation.
- Validation with mock data confirms robustness of the proposed framework.

## Abstract

AMS-02 on the International Space Station has been releasing data of unprecedented accuracy. This poses new challenges for their interpretation. We refine the methodology to get a statistically sound determination of the cosmic-ray propagation parameters. We inspect the numerical precision of the model calculation, nuclear cross-section uncertainties, and energy correlations in data systematic errors. We used the 1D diffusion model in USINE. Our $\chi^2$ analysis includes a covariance matrix of errors for AMS-02 systematics and nuisance parameters to account for cross-section uncertainties. Mock data were used to validate some of our choices. We show that any mis-modelling of nuclear cross-section values or the energy correlation length of the covariance matrix of errors biases the analysis. It also makes good models ($\chi^2_{\rm min}/{\rm dof}\approx1$) appear as excluded ($\chi^2_{\rm min}/{\rm dof}\gg1$). We provide a framework to mitigate these effects (AMS-02 data are interpreted in a companion paper). New production cross-section data and the publication by the AMS-02 collaboration of a covariance matrix of errors for each data set would be an important step towards an unbiased view of cosmic-ray propagation in the Galaxy.