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Particle Interaction and Propagation

Simulation of Extensive Air Showers

This Video was simulated using CORSIKA, showing the Cherenkov Footprint for 4 different primary particles. Colors indicate

the particle type that caused the Cherenkov radiation.

The Leptonpropagator PROPOSAL

PROPOSAL (PRopagator with Optimal Precision and Optimal Speed for All Leptons) is a Monte-Carlo Simulation library written in C++ with Python bindings. The original design goal was to simulate high energy muons traveling large distances through media with high performance and accuracy. This is needed for large volume detectors like neutrino telescopes or any other underground experiments dealing with an atmospheric muon background.

Currently, PROPOSAL is used for the propagation and decay of muons and taus in the simulation chain of IceCube and RNO. It will be used in the atmospheric shower simulation software CORSIKA 8 to calculate the electromagnetic component consisting of the propagation of electrons/positrons and high energy photons.

Further information can be found here.

CORSIKA

The Software Framework CORSIKA (COsmic Ray SImulations for KAscade) was developed for the simulation of complex atmospheric particle cascades induced by Cosmic-Rays up to the highest energies. Due to the complexity of the simulation with tens of thousands of particles and billions of photons the calculation time can go up to several hours or even days for a single cascade. With several million cumulative CPU hours per year, even small improvements can significantly reduce costs and enable better or new simulations.

With the long-standing and successful CORSIKA7 becoming technically older, there is currently work in progress for a complete rewritten CORSIKA8. This version will be written C++ and will use state of the art technical methods like python bindings and high parallel execution. In Dortmund we are working on CORSIKA with the background of the collaborate research center SFB876 (Providing Information by Resource-Constrained Data Analysis) by using various methods to reduce time and energy consumption.

Further information can be found here.