20.500.12556/RUL-164666 Learning the composition of ultrahigh energy cosmic rays We apply statistical inference on the Pierre Auger Open Data to discern the mass composition of cosmic rays at different energies. Working with longitudinal electromagnetic profiles of cosmic ray showers, in particular their peaking depths X$_{max}$, we employ central moments of the X$_{max}$ distributions to discriminate between different shower compositions. We find that already the first few moments entail the most relevant information to infer the primary cosmic ray mass spectrum. Our approach, based on an unbinned likelihood, allows us to consistently account for sources of statistical uncertainties due to finite datasets, both measured and simulated, as well as systematic effects. Finally, we provide a quantitative comparison of different high energy hadronic interaction models available in the atmospheric shower simulation codes. cosmic rays astroparticles detectors gravitation cosmology astrophysics statistical physics thermodynamics true false true Angleški jezik Ni določen Članek v reviji 2024-11-06 15:53:13 2024-11-06 15:53:14 2024-11-22 14:55:17 0000-00-00 00:00:00 2023 0 0 32 str. iss. 2, art. 022004 Vol. 108 2023 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 53 2470-0010 10.1103/PhysRevD.108.022004 159693827 PhysRevD.108.022004_(1).pdf PhysRevD.108.022004_(1).pdf 1 B392A9E0C4CC0901D45E3765753F4D4C e8cd2af5d8a948c971f0c8ad8b0b21ff326da3a40633c874649d65c3732a336a d121f421-9c4e-11ef-b232-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=195269 https://journals.aps.org/prd/abstract/10.1103/PhysRevD.108.022004 0 bf451765-9c4e-11ef-b232-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=195268 Fakulteta za matematiko in fiziko 0 0 0