Speaker
Description
The current generation of radio arrays has established radio detection as a viable technique for studying cosmic-ray composition through precise $X_{\max}$ measurements. The benchmark method for $X_{\max}$ reconstruction in radio detection involves fitting measured data to Monte-Carlo simulations, but this approach is computationally expensive. Alternative methods rely on parametrizations derived from such simulations. In this contribution, we present a novel and computationally efficient method based on the geometrical backtracking of radio signals measured by a ground-based antenna array, which requires only minimal input from simulations. The signal received by each antenna is considered to have travelled perpendicular to the radio wavefront, and is traced back to the shower axis, thereby reconstructing the radio emission profile of the extensive air shower. Applying this method to simulated cosmic-ray proton and iron showers in the energy range of $10^{17}-10^{18}\,\mathrm{eV}$, we observe a strong correlation between the reconstructed radio emission profile in the $20-80$ MHz frequency band and the longitudinal profile of the shower, enabling a reliable estimation of $X_{\max}$.