Discarded low energy particles in extensive air shower simulations: Effect on the shower Energy Deposit

TL;DR

This paper investigates how discarding low-energy particles in air shower simulations biases energy deposit estimates and proposes a correction method to improve accuracy, crucial for fluorescence detector data interpretation.

Contribution

It introduces a universal correction prescription for low-energy particle cuts in air shower simulations, reducing bias in energy deposit measurements.

Findings

Bias in energy deposit ranges from 3% to over 30% depending on the energy cut.

A 0.4 MeV electron and 0.9 MeV gamma cut is an effective compromise.

The correction method is independent of the energy cut value.

Abstract

The simulation of particle cascades initiated in the atmosphere by ultra high energy cosmic ray particles involves the generation and propagation of a huge amount of particles. As it is unpractical to follow every particle to its end, particles below a certain energy ($E_{Cut}$) are discarded from the simulation. In this article we study in detail the influence that this cut has on the total energy deposited in the atmosphere by the particle cascade in AIRES simulations. The energy deposit is directly related to the emission of fluorescence light and is critical for the accurate simulation of shower signals in fluorescence detectors. Not correcting for the discarded particles introduces a bias on several shower observables related to the energy deposit that can range from 3 to 30% or more depending on the $E_{Cut}$ value used. A prescription for the correct treatment of these particles is proposed, and the resulting corrections to the total energy deposit are addressed, including a new universal parametrization of the mean energy deposit per particle. The low energy cut is introduced in the simulations to reduce the required CPU time per shower at the expense of simulation accuracy. We find that a 0.4 MeV cut for electrons and 0.9 MeV cut for gammas is an adequate compromise, and that the proposed prescription is capablable of removing the bias introduced by this cut. The prescription is independent of the energy cut value and can be used to correct and compare simulations made with different energy cuts.