Related papers: Gamma/Hadron Separation in Imaging Air Cherenkov T…

The High Altitude Water Cherenkov observatory (HAWC) is an air shower array devised for TeV gamma-ray astronomy. HAWC is located at an altitude of 4100 m a.s.l. in Sierra Negra, Mexico. HAWC consists of 300 Water Cherenkov Detectors, each…

We describe the possibly measurable difference in the Cherenkov light component of EAS induced by an electromagnetic particle (e+, e- or gamma) and induced by a hadron (i.e. proton or heavier nuclei) in TeV range. The method can be applied…

Deep learning methods have resulted in significant performance improvements in several application domains and as such several software frameworks have been developed to facilitate their implementation. This paper presents a comparative…

TenTen is a proposed array of Imaging Atmospheric Cherenkov Telescopes (IACT) optimized for the gamma ray energy regime of 10 TeV to 100 TeV, but with a threshold of ~1 to a few TeV. It will offer a collecting area of 10 km2 above energies…

Latte (for LATent Tensor Evaluation) is a Python library for evaluation of latent-based generative models in the fields of disentanglement learning and controllable generation. Latte is compatible with both PyTorch and TensorFlow/Keras, and…

Arrays of imaging air Cherenkov telescopes (IACTs) like VERITAS, HESS have been recently proposed as the instruments of the next generation for ground based very high energy gamma-ray astronomy invading into 50-100 GeV energy range. Here we…

The TAIGA experimental complex is a hybrid observatory for high-energy gamma-ray astronomy in the range from 10 TeV to several EeV. The complex consists of such installations as TAIGA- IACT, TAIGA-HiSCORE and a number of others. The…

We introduce a new simulation and analysis paradigm for Imaging Atmospheric Cherenkov Telescope (IACT) arrays, simulating the actual observation conditions as well as individual telescope configuration for each observation unit. Compared to…

The MAGIC 17m-diameter Imaging Air Cherenkov Telescope (IACT) has been commissioned beginning of 2005. The telescope has been designed to achieve the lower detection energy threshold ever obtained with an IACT, about 50 GeV. A new window in…

This work is a methodical study of another option of the hybrid method originally aimed at gamma/hadron separation in the TAIGA experiment. In the present paper this technique was performed to distinguish between different mass groups of…

Cherenkov telescopes are also sensitive to the atmospheric fluorescence produced by the extensive air showers. However this contribution is neglected by the reconstruction algorithms of imaging air Cherenkov telescopes IACTs and wide-angle…

Unsupervised learning of disentangled representations is an open problem in machine learning. The Disentanglement-PyTorch library is developed to facilitate research, implementation, and testing of new variational algorithms. In this…

Deep convolutional neural networks (DCNs) are a promising machine learning technique to reconstruct events recorded by imaging atmospheric Cherenkov telescopes (IACTs), but require optimization to reach full performance. One of the most…

Neural networks used in computations with more advanced algebras than real numbers perform better in some applications. However, there is no general framework for constructing hypercomplex neural networks. We propose a library integrated…

Particle identification at the Super Charm-Tau factory experiment will be provided by a Focusing Aerogel Ring Imaging CHerenkov detector (FARICH). The specifics of detector location make proper cooling difficult, therefore a significant…

Deep metric learning algorithms have a wide variety of applications, but implementing these algorithms can be tedious and time consuming. PyTorch Metric Learning is an open source library that aims to remove this barrier for both…

Imaging Atmospheric Cherenkov Telescopes (IACTs) are ground-based instruments devoted to the study of very high energy gamma-rays coming from space. The detection technique consists of observing images created by the Cherenkov light emitted…

Two of the Key Science Projects of the Cherenkov Telescope Array (CTA) consist in performing a deep survey of the Galactic and Extragalactic sky, providing an unbiased view of the Universe at energies above tens of GeV. To optimize the time…

During the last decade ground-based very high-energy gamma-ray astronomy achieved a remarkable advancement in the development of the observational technique for the registration and study of gamma-ray emission above 100 GeV. It is widely…

We introduce nvTorchCam, an open-source library under the Apache 2.0 license, designed to make deep learning algorithms camera model-independent. nvTorchCam abstracts critical camera operations such as projection and unprojection, allowing…