Energy spectra of elemental groups of cosmic rays with the KASCADE experiment data and machine learning

Abstract

We report the reconstruction of the mass component spectra of cosmic rays (protons, helium, carbon, silicon and iron) and their mean mass composition, at energies from 1.4 to 100 PeV. The results are derived from the archival data of the extensive air shower experiment KASCADE. We use a novel machine learning technique developed specifically for this reconstruction, and post-LHC hadronic interaction models: QGSJet-II.04, EPOS-LHC and Sibyll 2.3c. We have found an excess of the proton component and a deficit of intermediate and heavy nuclei components compared to the original KASCADE results. The spectra of protons and helium show a knee-like behavior at ~ 4.4 PeV and ~ 11 PeV, with significances 5.2$\sigma$ and 3.9$\sigma$, respectively. The spectrum of the iron component has a hint (2.4$\sigma$) of a hardening at ~ 4.5 PeV, which can be interpreted as a counterpart of a hardening in the proton spectrum at 166 TeV, recently reported by the GRAPES-3 experiment. The systematic uncertainties of our analysis were found to be smaller than those of the original KASCADE, as well as those of IceTop and TALE experiments, over the most part of the energy range studied. We also estimated separately the uncertainty related to the difference between the three mentioned hadronic interaction models. We also compute a mean logarithm mass of cosmic ray flux as a function of energy. It is in agreement with the results of IceTop, TALE and LHAASO within the uncertainties.

arXiv commentaccepted to JCAP; significant content additions compared to the previous version

References in corpus (22)

• Scikit-learn: Machine Learning in Python
• TensorFlow: A system for large-scale machine learning
• EPOS LHC : test of collective hadronization with LHC data
• Monte Carlo treatment of hadronic interactions in enhanced Pomeron scheme: I. QGSJET-II model
• KASCADE measurements of energy spectra for elemental groups of cosmic rays: Results and open problems
• Cosmic ray event generator Sibyll 2.1
• QGSJET-II: towards reliable description of very high energy hadronic interactions
• Spectrum of cosmic-ray nucleons and the atmospheric muon charge ratio
• Hadronic interaction model Sibyll 2.3d and extensive air showers
• KASCADE-Grande measurements of energy spectra for elemental groups of cosmic rays
• Cosmic Ray Spectrum and Composition from PeV to EeV Using 3 Years of Data From IceTop and IceCube
• A Measurement of the Cosmic Ray Spectrum and Composition at the Knee
• Are protons still dominant at the knee of the cosmic-ray energy spectrum?
• Energy Spectra of Elemental Groups of Cosmic Rays: Update on the KASCADE Unfolding Analysis
• Escape model for Galactic cosmic rays and an early extragalactic transition
• Measurements of All-Particle Energy Spectrum and Mean Logarithmic Mass of Cosmic Rays from 0.3 to 30 PeV with LHAASO-KM2A
• The Cosmic-Ray Composition between 2 PeV and 2 EeV Observed with the TALE Detector in Monocular Mode
• The KASCADE Cosmic-ray Data Centre KCDC: Granting Open Access to Astroparticle Physics Research Data
• Cosmic ray mass composition at the knee using azimuthal fluctuations of air shower particles detected at ground by the KASCADE experiment
• New insights from old cosmic rays: A novel analysis of archival KASCADE data
• Latest Analysis Results from the KASCADE-Grande Data
• Methods of machine learning for the analysis of cosmic rays mass composition with the KASCADE experiment data

Cited by in corpus (5)

• LHAASO protons versus LHAASO diffuse gamma-rays: a consistency check
• Deep Learning the Forecast of Galactic Cosmic-Ray Spectra
• Cosmic ray mass composition measurement in the energy range from $10^{16.5}$ eV to $10^{18.5}$ eV observed with the TALE hybrid detector
• Joint constraint on the propagation origin of the cosmic-ray spectral knee from energy spectrum and anisotropy observations
• Cosmic-Ray Mass Composition around the Knee via Principal Component Analysis