Machine learning algorithms can learn the rules and patterns of big data through computers, excavate potential information hidden behind data, be widely used to solve classification, regression, clustering, other problems. Firstly, this paper uses CORSIKA software simulate process cosmic ray cascade shower in atmosphere, generating such as initial energy, zenith angle, azimuth angle particles. ...

Applying Machine Learning (ML) methods for the analysis of muon lateral distributions in Extensive Air Showers detected by citizen science projects, while taking into account spatial distribution detectors requires enormous training data sets. Therefore, generating these sets with typical Monte Carlo (MC) generators like CORSIKA is computationally prohibitive. Here we present a method which app...

Ionization showers are created in the Earth’s atmosphere by cosmic particles or by run-away electrons from pulsed discharges or by the decay of radioactive elements like radon and krypton. These showers provide pre-ionization that can play a role for discharge inception or evolution; radioactive admixtures in plasma technology use the same effect. While the CORSIKA program provides cross sectio...

Gamma ray bursts (GBRs) are a class of highly energetic explosions emitting radiation in a very short timescale of a few seconds and with a very narrow opening angle. Although, all GRBs observed so far are extragalactic in origin, there is a high probability of a GRB of galactic origin beaming towards the Earth in the past ~ 0.5 Gyr. We define the level of catastrophic damage to the biosphere a...

We discuss here Quantum molecular dynamics models (QMD) and Dual Parton Models (DPM and QGSM). We compare RHIC data to DPM–models and we present a (Cosmic ray oriented) model comparison. The emphasis of this contribution is to high energies, therefore, QMD non–relativistic models (E < 2AGeV) are not treated here. The first relativistic QMD model was RQMD [1]. This model is no longer supported s...