Towards an improved mass composition analysis with LOFAR
S. Buitink*, A. Corstanje, A. Bonardi, H. Falcke, B.M. Hare, J.R. Hörandel, T. Huege, G. Krampah, P. Mitra, A. Nelles, H. Pandya, J.P. Rachen, L. Rossetto, O. Scholten, S. ter Veen, T.N.G. Trinh and T. Winchen
Pre-published on:
July 22, 2019
Published on:
July 02, 2021
Abstract
The LOFAR radio telescope measures air showers in the energy range $10^{17}$ to $10^{18}$ eV. For each measured shower, the depth of shower maximum Xmax is reconstructed by simulating the radio signal for an ensemble of showers using Corsika and CoREAS. Fitting their radio ‘footprints’ on the ground to the measured radio data yields an Xmax estimate to a precision of about 20 g/cm$^2$. Compared to previous works, we have improved the method in several ways. Local atmospheric data and refractive index profiles are now included into the simulations. The energy estimate and the fitting procedure are now done using the radio signals only, thus limiting systematic uncertainties due to the particle detector array (LORA). Using selection criteria from a more elaborate characterisation of the radio and particle detection, we reduce a composition bias in the Xmax reconstruction. A possible residual bias has been bounded from above. Thus, the systematic uncertainties on <Xmax> have been lowered, reducing an important limiting factor for composition studies at any level of statistics.
DOI: https://doi.org/10.22323/1.358.0205
How to cite
Metadata are provided both in "article" format (very similar to INSPIRE) as this helps creating
very compact bibliographies which can be beneficial to authors and
readers, and in "proceeding" format
which is more detailed and complete.