Statistical Tools for Analyzing the Cosmic Ray Energy Spectrum

TL;DR

This paper develops un-binned statistical tools to analyze cosmic ray energy spectra, effectively detecting flux suppression and aiding astrophysical data interpretation.

Contribution

It introduces new statistical methods for analyzing cosmic ray spectra, including robust tests for flux suppression, applicable to various astrophysical data sets.

Findings

Evidence of flux suppression in simulated data

Effective un-binned statistical tools for spectral analysis

Methods applicable to other astrophysical power-law data

Abstract

In this paper un-binned statistical tools for analyzing the cosmic ray energy spectrum are developed and illustrated with a simulated data set. The methods are designed to extract accurate and precise model parameter estimators in the presence of statistical and systematic energy errors. Two robust methods are used to test for the presence of flux suppression at the highest energies: the Tail-Power statistic and a likelihood ratio test. Both tests give evidence of flux suppression in the simulated data. The tools presented can be generalized for use on any astrophysical data set where the power-law assumption is relevant and can be used to aid observational design.