Reconstructing Air Shower Parameters with MGMR3D

TL;DR

This paper introduces MGMR3D, a fast semi-analytic model for reconstructing air shower parameters from radio emission data, achieving high accuracy and efficiency compared to Monte Carlo methods.

Contribution

MGMR3D provides a rapid, semi-analytic approach to model radio footprints of air showers, enabling efficient parameter reconstruction with improved accuracy over previous models.

Findings

MGMR3D achieves strong agreement with Monte Carlo simulations.

It can reconstruct shower parameters with a $ ext{X}_{ ext{max}}$ resolution of 22 g/cm$^2$.

It attains an energy resolution of 19%.

Abstract

Measuring the radio emission from cosmic ray particle cascades has proven to be a very efficient method to determine their properties such as the mass composition. Efficient modeling of the radio emission from air showers is crucial in order to extract the cosmic ray physics parameters from the measured radio emission. MGMR3D is a fast semi-analytic code that calculates the complete radio footprint, i.e.\ intensity, polarization, and pulse shapes, for a parametrized shower-current density and can be used in a chi-square optimization to fit a given radio data. It is many orders of magnitude faster than its Monte Carlo counterparts. We provide a detailed comparative study of MGMR3D to Monte Carlo simulations, where, with improved parametrizations, the shower maximum $\Xmax$ is found to have very strong agreement with a small dependency on the incoming zenith angle of the shower. Another interesting feature we observe with MGMR3D is sensitivity to the shape of the longitudinal profile in addition to $\Xmax$. This is achieved by probing the distinguishable radio footprint produced by a shower having a different longitudinal profile than usual. Furthermore, for the first time, we show the results of reconstructing shower parameters for LOFAR data using MGMR3D, and obtaining a $\Xmax$ resolution of 22 g/cm$^2$ and energy resolution of 19\%.