# Cosmic Ray Spectrum and Composition from PeV to EeV Using 3 Years of Data From IceTop and IceCube

## TL;DR

This study uses three years of IceTop and IceCube data to measure the cosmic ray energy spectrum and composition from PeV to EeV energies, employing neural networks and multiple analysis methods.

## Contribution

It introduces a combined analysis approach using surface and in-ice detector data with neural networks to simultaneously determine cosmic ray spectrum and composition.

## Key findings

- All-particle spectrum measured across PeV to EeV range.
- Elemental group spectra reconstructed with systematic uncertainties analyzed.
- Comparison of two analysis methods highlights their respective advantages.

## Abstract

We report on measurements of the all-particle cosmic ray energy spectrum and composition in the PeV to EeV energy range using three years of data from the IceCube Neutrino Observatory. The IceTop detector measures cosmic ray induced air showers on the surface of the ice, from which the energy spectrum of cosmic rays is determined by making additional assumptions about the mass composition. A separate measurement is performed when IceTop data are analyzed in coincidence with the high-energy muon energy loss information from the deep in-ice IceCube detector. In this measurement, both the spectrum and the mass composition of the primary cosmic rays are simultaneously reconstructed using a neural network trained on observables from both detectors. The performance and relative advantages of these two distinct analyses are discussed, including the systematic uncertainties and the dependence on the hadronic interaction models, and both all-particle spectra as well as individual spectra for elemental groups are presented.