相关论文: The Preliminary Results on Analysis of TAIGA-IACT …
The Cherenkov Telescope Array (CTA), conceived as an array of tens of imaging atmospheric Cherenkov telescopes (IACTs), is an international project for a next-generation ground-based gamma-ray observatory, aiming to improve on the…
Telescopes based on the imaging atmospheric Cherenkov technique (IACTs) detect images of the atmospheric showers generated by gamma rays and cosmic rays as they are absorbed by the atmosphere. The much more frequent cosmic-ray events form…
Imaging atmospheric Cherenkov telescopes (IACTs) are used to observe very high-energy photons from the ground. Gamma rays are indirectly detected through the Cherenkov light emitted by the air showers they induce. The new generation of…
Our Galaxy is filled with cosmic-ray particles and more than 98% of them are atomic nuclei. In order to clarify their origin and acceleration mechanism, chemical composition measurements of these cosmic rays with wide energy coverage play…
The Cherenkov Telescope Array (CTA) will be the world's largest and most sensitive ground-based gamma-ray observatory in the energy range from a few tens of GeV to tens of TeV. The LST-1 prototype, currently in its commissioning phase, is…
Modern Imaging Atmospheric Cherenkov Telescopes (IACTs) generate a huge amount of data that must be classified automatically, ideally in real time. Currently, machine learning-based solutions are increasingly being used to solve…
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…
CTLearn is a new Python package under development that uses the deep learning technique to analyze data from imaging atmospheric Cherenkov telescope (IACT) arrays. IACTs use the Cherenkov light emitted from air showers, initiated by…
Imaging atmospheric Cherenkov telescopes (IACTs) detect gamma rays by measuring the Cherenkov light emitted by secondary particles in the air shower when the gamma rays hit the atmosphere. At low energies, the limited amount of Cherenkov…
Based on the Monte Carlo simulations we have studied the performance of the HEGRA system of imaging air Cherenkov telescopes (IACTs) in its present configuration of 4 IACTs as well as in its future final configuration of 5 IACTs. Here we…
In order to better utilize the information contained in the shower images generated by imaging Cherenkov telescopes (IACTs) equipped with cameras with small pixels, images are fit to a parametrization of image shapes gained from Monte Carlo…
We investigate possible sky survey modes with the Middle Sized Telescopes (MST, aimed at covering the energy range from $\sim$100 GeV to 10 TeV) subsystem of the Cherenkov Telescope Array (CTA). We use the standard CTA tools, CORSIKA and…
The Cherenkov Telescope Array (CTA) is the next-generation stereoscopic system of Imaging Atmospheric Cherenkov Telescopes (IACTs). In IACTs, the atmosphere is used as a calorimeter to measure the energy of extensive air showers induced by…
New deep learning techniques present promising new analysis methods for Imaging Atmospheric Cherenkov Telescopes (IACTs) such as the upcoming Cherenkov Telescope Array (CTA). In particular, the use of Convolutional Neural Networks (CNNs)…
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…
The Cherenkov Telescope Array (CTA) is the future observatory for ground-based imaging atmospheric Cherenkov telescopes. Each telescope will provide a snapshot of gamma-ray induced particle showers by capturing the induced Cherenkov…
Cherenkov gamma telescope observes high energy gamma rays, taking advantage of the radiation emitted by charged particles produced inside the electromagnetic showers initiated by the gammas, and developing in the atmosphere. The detector…
Imaging Atmospheric Cherenkov Telescopes (IACTs) detect very-high-energy gamma rays from ground level by capturing the Cherenkov light of the induced particle showers. Convolutional neural networks (CNNs) can be trained on IACT camera…
We suggest a new approach to study the cosmis ray (CR) mass composition in the energy region from 30 TeV/nucleus up to the "knee" region, i.e. up to a few PeV/nucleus, using an array of imaging atmospheric Cherenkov telescopes (IACTs) of a…
The Cherenkov Telescope Array Observatory (CTAO), a next-generation ground-based gamma-ray observatory, will be composed of two arrays of multiple imaging atmospheric Cherenkov telescopes (IACTs) located in both the Northern and Southern…