|
|
|
see also [ICRC2019](ICRC2019)
|
|
|
|
see also [ICRC2021](ICRC2021)
|
|
|
|
|
|
|
|
# ICRC2023 author list (preliminary):
|
|
|
|
|
|
|
|
As of now identically to the 2021 one, this might change
|
|
|
|
https://gitlab.iap.kit.edu/AirShowerPhysics/corsika/-/wikis/CORSIKA-Talks/ICRC2021-author-list
|
|
|
|
|
|
|
|
# ICRC2023 talks:
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
## Nikolaos Karastathis
|
|
|
|
|
|
|
|
### Simulating radio emission from air showers with CORSIKA 8
|
|
|
|
|
|
|
|
CORSIKA 8 (C8) is a new framework for air shower simulations implemented in modern C++17, based on past experience with existing codes like CORSIKA 7 (C7). The flexible and modular structure of the project allows the development of independent modules that can produce a fully customizable air shower simulation. The radio module in particular, is designed to filter relevant particle properties from the simulated particle showers, treat the signal propagation and electric field calculation to each antenna in an autonomous and flexible way. Our module provides the possibility to simulate simultaneously the radio emission calculated with two independent formalisms, namely the “Endpoints” and “ZHS”. The key feature of the module’s design is the fact that it sets the standard on how to take advantage of C8’s novel environment and geometry and provides a straightforward interface for one to expand upon and simulate specific physical scenarios. In this work, we will present an air shower simulation comparison study of comparable showers generated with C8, C7 and ZHAireS.
|
|
|
|
|
|
|
|
## Tim Huege
|
|
|
|
|
|
|
|
### The particle-shower simulation code CORSIKA 8
|
|
|
|
|
|
|
|
https://www.overleaf.com/4758124133nqjdgmcxjwkj
|
|
|
|
|
|
|
|
CORSIKA up to version 7 has been the most-used Monte Carlo code for simulating extensive air showers for more than 20 years. Due to its monolithic, Fortran-based software design and hand-optimized code, however, it has become difficult to maintain, adapt to new computing paradigms and extend for more complex simulation needs. These limitations led to the CORSIKA 8 project, which constitutes a complete rewrite of the CORSIKA 7 core functionality in a modern, modular C++ framework. CORSIKA 8 has now reached a state that we consider ``physics-complete''. It already supports the treatment of hadronic interactions with SIBYLL 2.3d, QGSJETII-04, EPOS-LHC and PYTHIA 8.3 and the treatment of the electromagnetic cascade with PROPOSAL 7.6. Particular highlights are multi-interaction-media support, including cross-media particle showers, and an advanced calculation of the radio emission from particle showers. CORSIKA 8 has also reached a stability that already allows experts to engage in development for specific applications. In this contribution, we discuss the design principles of CORSIKA 8, give an overview of the functionality implemented to date, the validation of its simulation results, and the plans for its further development.
|
|
|
|
|
|
|
|
|
|
|
|
## Dominik Baack
|
|
|
|
|
|
|
|
### Comparison and efficiency of GPU accelerated optical light propagation in CORSIKA8
|
|
|
|
|
|
|
|
https://www.overleaf.com/read/qpyjpjwstfcy
|
|
|
|
|
|
|
|
AI accelerators have proliferated in data centres in recent years and are now almost ubiquitous. In addition, their computational power and, most importantly, their energy efficiency are up to orders of magnitude higher than that of traditional computing. In recent years, various methods and optimisations have been tested to use these hybrid systems for simulations in the context of astroparticle physics.
|
|
|
|
|
|
|
|
|
|
|
|
The main focus of this talk is the propagation of optical, i.e. flourescence and Cherenkov, photons through thin inhomogeneous media. Different techniques used and approximations, e.g. the atmospheric model, tested during the development will be presented. The trade-off between performance and precision allows the experiment to achieve its physical precision limited to the real resolution of the experiment and not invest power and time and vanishing precision gains. The additional comparison of classical CPU-based simulations with the new methods validates these methods and allows evaluation against a known baseline. |