Related papers: Developing a Machine Learning Algorithm-Based Clas…
Cherenkov telescope experiments, such as H.E.S.S., have been very successful in astronomical observations in the very-high-energy (VHE; E $>$ 100 GeV) regime. As an integral part of the detector, such experiments use Earth's atmosphere as a…
Observations with the Cherenkov telescopes are in principle limited to the clear sky conditions due to significant absorption of Cherenkov light by clouds. If the cloud level is high enough or the atmospheric transmission of the cloud is…
When very-high-energy gamma rays interact high in the Earth's atmosphere, they produce cascades of particles that induce flashes of Cherenkov light. Imaging Atmospheric Cherenkov Telescopes (IACTs) detect these flashes and convert them into…
A Monte-Carlo study to reconstruct energy and mass of cosmic rays with energies above 300 TeV using ground based measurements of the electromagnetic part of showers initiated in the atmosphere is presented. The shower properties determined…
Atmospheric Cherenkov technique is an established methodology to study TeV energy gamma rays. Here we carry out systematic monte carlo simulation studies of the timing information of Cherenkov photons. Extensive studies have already been…
Machine learning, through the use of convolutional and recurrent neural networks is a promising avenue for the improvement of background rejection performance in imaging atmospheric Cherenkov telescopes. However, it is of paramount…
In gamma ray astronomy with Cherenkov telescopes, machine learning models are needed to guess what kind of particles generated the detected light, and their energies and directions. The focus in this work is on the classification task,…
The dominant background for observations of gamma-rays in the energy region above 50 GeV with Imaging Atmospheric Cherenkov telescopes are cosmic-ray events. The images of most of the cosmic ray showers look significantly different from…
This paper presents several approaches to deal with the problem of identifying muons in a water Cherenkov detector with a reduced water volume and 4 PMTs. Different perspectives of information representation are used and new features are…
A new SPHERE-3 telescope is being developed for cosmic rays spectrum and mass composition studies in the 5--1000 PeV energy range. Registration of extensive air showers using reflected Cherenkov light method applied in the SPHERE detector…
Imaging atmospheric Cherenkov telescope (IACT) arrays record images from air showers initiated by gamma rays entering the atmosphere, allowing astrophysical sources to be observed at very high energies. To maximize IACT sensitivity,…
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…
Extensive air showers created by high-energy particles interacting with the Earth atmosphere can be detected using imaging atmospheric Cherenkov telescopes (IACTs). The IACT images can be analyzed to distinguish between the events caused by…
Radio Cherenkov emission underlines detection of high energy particles via a signal growing like the particle-energy-squared. Cosmic ray-induced electromagnetic showers are a primary application. While many studies have treated the…
A Monte-Carlo study is presented using ground based measurements of the electromagnetic part of showers initiated in the atmosphere by high energetic cosmic rays to reconstruct energy and mass of primary particles with energies above 300…
In Monte-Carlo simulations of gamma-ray or cosmic-ray detector arrays on the ground (here mainly arrays of imaging atmospheric Cherenkov telescopes), the atmosphere enters in several ways: in the development of the particle showers, in the…
Using detailed simulations of calorimeter showers as training data, we investigate the use of deep learning algorithms for the simulation and reconstruction of particles produced in high-energy physics collisions. We train neural networks…
A method for fast simulation of the Cherenkov light generated by electromagnetic showers is described. The parametrization for the longitudinal profile is used and fluctuations and correlations of the parameters are taken into account in a…
The Cosmic Multiperspective Event Tracker (CoMET) R&D project aims to optimize the techniques for the detection of soft-spectrum sources through very-high-energy gamma-ray observations using particle detectors (called ALTO detectors), and…
In this work, we present a new, high performance algorithm for background rejection in imaging atmospheric Cherenkov telescopes. We build on the already popular machine-learning techniques used in gamma-ray astronomy by the application of…