Speaker
Description
The reconstruction of inclined extensive air showers from radio measurements, even though extensively researched, still holds room for improvement. In this contribution, we will present a new method for reconstructing inclined extensive air showers from radio measurements based on Information Field Theory. This Bayesian approach is based on a full forward model of air shower radio emission from the main observables (electromagnetic energy, distance to shower maximum, arrival direction) to the electric field. As a semi-parametric model, it includes not only established parametrisations of the radio emission, but also accounts for deviations from these parametrisations using Gaussian processes. Noise from narrowband emitters is also modelled explicitly, alleviating the necessity for filtering. Tests on simulations, including measured noise and a realistic instrument response, have shown that this method reaches an energy resolution of 5%, a resolution in the distance to the shower maximum of 5%, and an angular resolution of $0.03^\circ$ in azimuth and $0.04^\circ$ in zenith. For the first time, this method combines the reconstruction of the electric field, the electromagnetic energy and the arrival direction, with a performance that ranges from competitive to exceeding that of established methods.