Measurements of the cosmic ray composition with air shower experiments

2013

EPJ Web of Conferences

Abstract. Currently the uncertainty in the prediction of shower observables for different primary particles and energies is dominated by differences between hadronic interaction models. The LHC data on minimum bias measurements can be used to test Monte Carlo generators and these new constrains will help to reduce the uncertainties in air shower predictions. In this article, after a short introduction on air showers we will show the results of the comparison between the updated version of high energy hadronic interaction models with LHC data. Results for air shower simulations and their consequence on the comparison with air shower data will be discussed.

Section: Discussionmentioning

confidence: 99%

Connecting accelerator experiments and cosmic ray showers

2013

EPJ Web of Conferences

“…This uncertainty is comparable to the experimental uncertainty in the measurement of X max and the elongation rate is now the same for all models for a constant composition. As a consequence the interpretation of the data using a post-LHC model will be more reliable, especially concerning the possible change in mass composition with energy as summarized in [54].…”

Section: Discussionmentioning

confidence: 99%

Review of Model Predictions for Extensive Air Showers

Proceedings of 2016 International Conference on Ultra-High Energy Cosmic Rays (UHECR2016)

2018

In detailed air shower simulations, the uncertainty in the prediction of shower observable for different primary particles and energies is currently dominated by differences between hadronic interaction models. With the results of the first run of the LHC, the difference between post-LHC model predictions has been reduced at the same level as experimental uncertainties of cosmic ray experiments. At the same time new types of air shower observables, like the muon production depth, have been measured, adding new constraints on hadronic models. Currently no model is able to reproduce consistently all mass composition measurements possible with the Pierre Auger Observatory for instance. We review the current model predictions for various particle production observables and their link with air shower observables and discuss the future possible improvements.

Section: Discussionmentioning

confidence: 99%

Modelling hadronic interactions in cosmic ray Monte Carlo generators

2015

EPJ Web of Conferences

Abstract. Currently the uncertainty in the prediction of shower observables for different primary particles and energies is dominated by differences between hadronic interaction models. The LHC data on minimum bias measurements can be used to test Monte Carlo generators and these new constraints will help to reduce the uncertainties in air shower predictions. In this article, after a short introduction on air showers and Monte Carlo generators, we will show the results of the comparison between the updated version of high energy hadronic interaction models EPOS LHC and QGSJETII-04 with LHC data. Results for air shower simulations and their consequences on comparisons with air shower data will be discussed.