Effect of multiple reusing of simulated air showers in detector simulations

TL;DR

This paper investigates how reusing simulated air showers multiple times affects the accuracy of detector simulations and composition analysis in high-energy cosmic ray research.

Contribution

It provides a detailed analysis of the artificial biases introduced by reusing single air showers in Monte Carlo simulations, especially in kernel density estimators.

Findings

Reusing showers introduces artificial correlations in simulations.

Repetition impacts the accuracy of kernel density estimators.

Multiple reuse can bias composition studies.

Abstract

The study of high energy cosmic rays requires detailed Monte Carlo simulations of both, extensive air showers and the detectors involved in their detection. In particular, the energy calibration of several experiments is obtained from simulations. Also, in composition studies simulations play a fundamental role because the primary mass is determined by comparing experimental with simulated data. At the highest energies the detailed simulation of air showers is very costly in processing time and disk space due to the large number of secondary particles generated in interactions with the atmosphere. Therefore, in order to increase the statistics, it is quite common to recycle single showers many times to simulate the detector response. As a result, the events of the Monte Carlo samples generated in this way are not fully independent. In this work we study the artificial effects introduced by the multiple use of single air showers for the detector simulations. In particular, we study in detail the effects introduced by the repetitions in the kernel density estimators which are frequently used in composition studies.