Data-driven hadronic interaction model for atmospheric lepton flux calculations

TL;DR

This paper introduces a data-driven hadronic interaction model that reduces uncertainties in atmospheric lepton flux predictions by utilizing accelerator data, improving the accuracy of neutrino flux calculations for telescopes.

Contribution

It presents a novel parametrization of particle yields from accelerator data, integrated into the MCEq package, enabling more precise atmospheric neutrino flux estimates.

Findings

Smaller uncertainties in muon and neutrino flux predictions.

Good agreement with atmospheric flux data.

Enhanced flexibility for flux error estimation.

Abstract

The leading contribution to the uncertainties of atmospheric neutrino flux calculations arise from the cosmic-ray nucleon flux and the production cross sections of secondary particles in hadron-air interactions. The data-driven model developed in this work parametrizes particle yields from fixed-target accelerator data. The propagation of errors from the accelerator data to the inclusive muon and neutrino flux predictions results in smaller uncertainties than in previous estimates, and the description of atmospheric flux data is good. The model is implemented as part of the MCEq package, and hence can be flexibly employed for theoretical flux error estimation at neutrino telescopes.