Prospects for the detection of gamma rays using Cherenkov telescopes enhanced by a ground array observatory

TL;DR

This work investigates a hybrid observatory that places SST-1M Cherenkov telescopes inside a SWGO-like water-Cherenkov detector array to boost very-high-energy gamma-ray performance. Using detailed Monte Carlo simulations, the authors quantify improvements in gamma/hadron separation and flux sensitivity by incorporating WCD-derived observables LCm and P_tail_alpha into a Random Forest classifier, for both monocular and stereoscopic SST-1M operations. They report sensitivity gains of approximately 60% for monocular and 30% for stereoscopic modes above 10 TeV, driven mainly by enhanced muon-content discrimination, with additional benefits in energy calibration and rapid follow-up of transients. The study also discusses practical operational challenges and advantages of a high-altitude hybrid system, including cooling, power, duty cycle considerations, and cross-validation opportunities between IACTs and WCDs.

Abstract

We consider the Single-Mirror Small-Size imaging atmospheric Cherenkov Telescopes (SST-1M) to be located inside a high-altitude array of Water-Cherenkov Detectors (WCDs) inspired by the Southern Wide-field Gamma-ray Observatory (SWGO). For such a hybrid observatory, using detailed Monte Carlo simulations, we show an improvement in the flux sensitivity of monocular and stereoscopic SST-1M observation by about 60% and 30% above 10 TeV, respectively, due to the improved gamma/hadron separation when additional parameters from the WCD array are used. We also discuss further benefits of the hybrid SWGO concept and its technical challenges.

Figures (7)

• Figure 1: ROC curves in the monocular observation regime. Shown for a single SST-1M telescope alone (blue) and for SST-1M together with $\gamma$/h discrimination parameters obtained from the particle-detector array, including $P^{\alpha}_{\rm{tail}}$ (green), $LCm$ (red), both $P^{\alpha}_{\rm{tail}}$ and $LCm$ (orange), and true number of muons $N_{\mu}$ (purple). All curves are shown for energies above 10 TeV.
• Figure 2: Gini importance of features used in the Random Forests classifiers that separate $\gamma$ rays from hadrons. The analyses that use sole SST-1M telescope (blue) and SST-1M telescope with additional information from the particle-detector array are shown: true $N_{\mu}$ (purple), $LCm$ (red), $P^{\alpha}_{\rm{tail}}$ (green), and $P^{\alpha}_{\rm{tail}}$+$LCm$ (orange). Only the most important features are depicted, while the contribution of the rest of them, listed in the text, is summed and shown as Others.
• Figure 3: Flux sensitivity for a sole SST-1M telescope (blue) and one SST-1M with the additional information from the particle-detector array. The color coding is the same as in Fig \ref{['fig:roc_mono']}. A point-like source at the zenith angle of 20° observed for 50 h is assumed.
• Figure 4: ROC curves in the stereoscopic observation regime. Shown for a pair of SST-1M telescopes alone (blue) and for SST-1Ms together with $\gamma$/h discrimination parameters similarly to Fig. \ref{['fig:roc_mono']}. All curves are shown for energies above 10 TeV.
• Figure 5: Gini importance of features used in the Random Forests classifiers when stereoscopic observation is assumed. Identical color coding as in Fig. \ref{['fig:gini_mono']} is used, as well as the summed quantities in Others are the same.