On the accuracy of the primary energy and nuclei determination at mountain altitudes and sea level

Chilingarian, A.; Ter–Antonyan, S.; Vardanyan, A.; Gils, H.J.; Knapp, J.; Rebel, H.; Roth, M.

doi:10.1016/s0920-5632(96)00895-x

Cited by 4 publications

(1 citation statement)

References 6 publications

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“…The first way is a statistical method which unfolds the primary energy spectra from the corresponding integral equation set based on a detected EAS data set and the model of the EAS development in the atmosphere [5][6][7][8][9]. The second method is based on an eventby-event evaluation [2,[10][11][12][13] of the primary energy of the detected EAS with parameters q ≡ q(N e , N µ , N h , s, θ) using parametric E = f (q) [2,10,11,13] or non-parametric [12] energy estimator previously determined on the basis of shower simulations in the framework of a given model of EAS development.…”

Section: Introductionmentioning

confidence: 99%

An all-particle primary energy spectrum in the 3–200 PeV energy range

Garyaka

Мартиросов

Ter–Antonyan

et al. 2008

J. Phys. G: Nucl. Part. Phys.

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We present all-particle primary cosmic-ray energy spectrum in the 3 · 10 6 − 2 · 10 8 GeV energy range obtained by a multi-parametric event-by-event evaluation of the primary energy. The results are obtained on the basis of an expanded EAS data set detected at mountain level (700 g/cm 2 ) by the GAMMA experiment. The energy evaluation method has been developed using the EAS simulation with the SIBYLL interaction model taking into account the response of GAMMA detectors and reconstruction uncertainties of EAS parameters. Nearly unbiased (< 5%) energy estimations regardless of a primary nuclear mass with an accuracy of about 15−10% in the 3 · 10 6 − 2 · 10 8 GeV energy range respectively are attained.An irregularity ('bump') in the spectrum is observed at primary energies of ∼ 7.4 · 10 7 GeV. This bump exceeds a smooth power-law fit to the data by about 4 standard deviations. Not rejecting stochastic nature of the bump completely, we examined the systematic uncertainties of our methods and conclude that they cannot be responsible for the observed feature.

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