A Neural Network-Based Monoscopic Reconstruction Algorithm for H.E.S.S. II

Understand

The H.E.S.S.

• experiment entered its phase II with the addition of a new, large telescope named CT 5 that was added to the centre of the existing array of four smaller telescopes.
• The new telescope is able to detect fainter air showers due to its larger mirror area, thereby lowering the energy threshold of the array from a few hundred GeV down to $\mathcal{O}(50\,\textrm{GeV})$.
• Due to the power-law decrease of typical {\gamma}-ray and cosmic-ray spectra of astrophysical sources a majority of detected air showers are of low energies, thus being detected by CT 5 only, which motivates the need for a reconstruction algorithm based on information from CT 5 alone.