Speaker
Description
The Low Frequency Array (LOFAR) has been measuring cosmic rays for over a decade. Its dense core of antenna fields makes it an ideal tool for studying the radio emission of extensive air showers, sensitive to energies between $10^{16.5}$ eV and $10^{18}$ eV. Each air shower is recorded using a small particle detector array and hundreds of antennas. The current state-of-the-art method for reconstructing properties such as the shower maximum ($X_\text{max}$) relies on a $\chi^2$ fit of the measured electric field fluence data to a range of simulations and achieves the highest precision to date. However, reconstructing on the fluence-level, it does not fully utilize all available information from the data, the full time-dependent electric field, and is computationally intensive.
We present the current state of development of a new, holistic approach using Information Field Theory (IFT) that incorporates all available information within the data, and combines both particle detector and antenna data. This method uses probabilistic forward modeling of the radio signal and offers a physics-informed, simulation-independent reconstruction. Additionally, by treating the signal as a random field, IFT can simultanously provide uncertainty quantification.
The reconstruction takes the voltage traces and antenna positions and will yield time dependent electric fields at any ground position of the shower footprint, along with reconstruction parameters such as the depth of shower maximum ($X_\text{max}$), the cosmic ray energy $E$ and the direction of the cosmic ray as the forward model is dependent on these parameters.
| Collaboration(s) | LOFAR Key Science Project Cosmic Rays |
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