English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

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 dataof the extensive air shower experiment KASCADE. We use a novel machine learningtechnique, developed specifically for this reconstruction, and modern hadronicinteraction models: QGSJet.II-04, EPOS-LHC and Sibyll 2.3c. We have found amarked excess of the proton component and deficit of intermediate and heavynuclei components, compared to the original KASCADE results. At the same timeour results are partially consistent with the results of IceTop and TALEexperiments. The systematic uncertainties are computed taking into account thedifference between the hadronic models and have a similar magnitude as theuncertainties of other mentioned experiments, that were computed withoutcross-hadronic model systematics.

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