Superposition model for energy reconstruction and mass identification in cosmic ray spectra
Hu Liu, Fanping Li, J. Zhao, L. Y. Wang, Zhe Li, and S. Z. Chen

TL;DR
This paper introduces a superposition model-based method for reconstructing cosmic ray energy and mass composition using LHAASO data, achieving high resolution and low bias across a wide energy range.
Contribution
A novel superposition model approach for energy and mass reconstruction in cosmic rays, utilizing universal calibration lines and density measurements, improving accuracy over existing methods.
Findings
Energy resolution below 5% to 15% above 1 PeV.
Mass resolution for iron below 25% above 10 PeV.
Biases within ±5% for energy and ±0.3 for lnA below 40° zenith angle.
Abstract
The "knee" of cosmic ray spectra may reflect the maximum energy accelerated by galactic cosmic ray sources or the limit of the galaxy's ability to bind cosmic rays. Measurements of individual energy spectra are a crucial tool to understand the origin of the knee. Energy reconstruction and composition identification are foundations of the individual energy spectra measurements. One of the main scientific goals of Large High Altitude Air Shower Observatory (LHAASO) is measuring the cosmic ray energy spectra and composition from ~10 TeV to ~EeV. In this work, a novel method for reconstructing energy and logarithm mass (lnA) based on a superposition model is introduced. Energy and lnA are reconstructed using two universal, composition- and energy-independent calibration lines. For zenith angle below 40 degree, the energy and lnA biases are within +-5% and +-0.3, respectively, across all…
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Taxonomy
TopicsAstrophysics and Cosmic Phenomena · Dark Matter and Cosmic Phenomena · Radiation Therapy and Dosimetry
