Related papers: Gamma/hadron segregation for a ground based imagin…

Cherenkov Telescope Array (CTA) is an upcoming instrument that will start a new generation of atmospheric Cherenkov telescopes. CTA is expected not only to provide an unprecedented sensitivity in the tens of GeV to hundreds of TeV range,…

The next generation of observatories will facilitate the discovery of new types of astrophysical transients. The detection of such phenomena, whose characteristics are presently poorly constrained, will hinge on the ability to perform blind…

Nuclear reactors produce a high flux of MeV-scale antineutrinos that can be observed through inverse beta-decay (IBD) interactions in particle detectors. Reliable detection of reactor IBD signals depends on suppression of backgrounds, both…

This paper presents an autonomous approach to tree detection and segmentation in high resolution airborne LiDAR that utilises state-of-the-art region-based CNN and 3D-CNN deep learning algorithms. If the number of training examples for a…

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…

Random forest (RF) methodology is one of the most popular machine learning techniques for prediction problems. In this article, we discuss some cases where random forests may suffer and propose a novel generalized RF method, namely…

We present a new method of image cleaning for imaging atmospheric Cherenkov telescopes. The method is based on the utilization of wavelets to identify noise pixels in images of gamma-ray and hadronic induced air showers. This method selects…

This paper presents a method to identify electrons using the Cherenkov light emitted when a charged particle travels in air and photons are detected with a Silicon PhotoMultiplier (SiPM). The analysis is based on a photon-counting approach…

We present a sophisticated gamma-ray likelihood reconstruction technique for Imaging Atmospheric Cerenkov Telescopes. The technique is based on the comparison of the raw Cherenkov camera pixel images of a photon induced atmospheric particle…

Gamma-hadron discrimination based on shower observables is essential for identifying gamma-ray astrophysical sources at the highest energies. In this work, we introduce $P^{\alpha, T}_{\rm tail}$, a new discrimination variable for…

High energy gamma-ray astronomy has been established during the last decade through the launch of the Compton Gamma Ray Observatory (CGRO) and the success of its ground-based counterpart, the imaging atmospheric Cherenkov technique. In the…

Based on the DUSTGRAIN-pathfinder suite of simulations, we investigate observational degeneracies between nine models of modified gravity and massive neutrinos. Three types of machine learning techniques are tested for their ability to…

In this paper, we present the results of Monte Carlo simulations of atmospheric showers induced by diffuse gamma rays as detected by the high-energy gamma ray astronomy (HEGRA) system of five imaging atmospheric Cerenkov telescopes (IACTs).…

Indirect detection of gamma rays with ground-based observatories is currently the most sensitive experimental approach to characterize the gamma-ray sky at energies $>0.1$\,TeV. Ground-based detection of gamma-rays relies on the…

Context. The presence of clouds during observations with Imaging Atmospheric Cherenkov Telescopes can strongly affect the performance of the instrument due to additional absorption of light and scattering of light beyond the field of view…

Over the last three decades, the ground-based technique of imaging atmospheric Cherenkov telescopes has established itself as a powerful scientific discipline. About 250 very high gamma-ray sources of both galactic and extragalactic origin…

The Cherenkov Telescope Array is the next generation of observatory using imaging air Cherenkov technique for very-high-energy gamma-ray astronomy. Its first prototype telescope is operational on-site at La Palma and its data acquisitions…

Random Forest is a machine learning method that offers many advantages, including the ability to easily measure variable importance. Class balancing technique is a well-known solution to deal with class imbalance problem. However, it has…

The trajectory of a primary gamma-ray detected with an array of at least four atmospheric Cherenkov imaging telescopes can be reconstructed from the shower image centroid positions and geometrical considerations independent of the primary…

Telescopes, designed with semi-conductor based photo sensors, have the potential to detect Cherenkov or fluorescence light emitted by cosmic-rays in the atmosphere. Such telescopes promise a high duty cycle and efficiency in remote harsh…