Abstract
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
5.2σ and 3.9σ, respectively. The spectrum of the iron component has a
hint (2.4σ) 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
CR flux as a function of energy. It is in agreement with the results of IceTop, TALE and LHAASO
within the uncertainties.