Data Reduction for CORSIKA

Abstract

For the analysis of measured data by experiments, simulated Monte Carlo data is essential. It is used to test the understanding of the experiment, for separation of signal and background and for reconstruction of real physical properties from observable parameters. With increasing size of the experiments, more and more simulated data is needed. To optimize the simulation and to reduce the huge amount of calculation time needed, two different methods exist. The first method is the low-level optimization of the source code. The second one is the reduction of the actually needed Monte Carlo data. This report focuses on the cosmic ray simulation CORSIKA, which simulates cosmic ray induced particle showers within the atmosphere. In case of CORSIKA, big parts of the program are already optimized. Additionally, parts of the source code are only accessible in binary form so the first method of optimization is nearly impossible. Therefore the preferred method here is the reduction of unnecessarily generated data. This report presents a modified and extended internal structure for CORSIKA, which is shown in Figure 2. The modifications can be divided in two modules: Dynamic Stack and Remote Control. Both have complementary approaches to reduce the amount of needed simulation cycles and provide an easy API for customizations without assuming any of the CORSIKA code or structure.