$F_\gamma$: a new observable for photon-hadron discrimination in hybrid air shower events

TL;DR

The paper introduces $F_ extgamma$, a new observable derived from hybrid air shower data, which significantly improves photon-hadron discrimination in ultra-high-energy cosmic ray detection.

Contribution

It presents $F_ extgamma$, a novel, stable, and effective observable for photon-hadron separation that outperforms existing methods like $X_ ext{max}$ in hybrid air shower measurements.

Findings

$F_ extgamma$ achieves over 97.8% background rejection at 1 EeV.

$F_ extgamma$ outperforms $X_ ext{max}$ in photon-hadron separation.

The observable is stable against array irregularities and applicable across the full energy range.

Abstract

To search for ultra-high-energy photons in primary cosmic rays, air shower observables are needed that allow a good separation between primary photons and primary hadrons. We present a new observable, $F_\gamma$, which can be extracted from ground-array data in hybrid events, where simultaneous measurements of the longitudinal and the lateral shower profile are performed. The observable is based on a template fit to the lateral distribution measured by the ground array with the template taking into account the complementary information from the measurement of the longitudinal profile, i.e. the primary energy and the geometry of the shower. $F_\gamma$ shows a very good photon-hadron separation, which is even superior to the separation given by the well-known $X_\text{max}$ observable (the atmospheric depth of the shower maximum). At energies around $1\,\text{EeV}$ ($10\,\text{EeV}$), $F_\gamma$ provides a background rejection better than $97.8\,\%$ ($99.9\,\%$) at a signal efficiency of $50\,\%$. Advantages of the observable $F_\gamma$ are its technical stability with respect to irregularities in the ground array (i.e. missing or temporarily non-operating stations) and that it can be applied over the full energy range accessible to the air shower detector, down to its threshold energy. Furthermore, $F_\gamma$ complements nicely to $X_\text{max}$ such that both observables can well be combined to achieve an even better discrimination power, exploiting the rich information available in hybrid events.