Related papers: Developing a Machine Learning Algorithm-Based Clas…
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…
The Cherenkov Telescope Array is expected to lead to the detection of many new supernova remnants in the TeV and multi-TeV range. In addition to the individual study of each SNR, the study of these objects as a population can help…
This research note concerns the application of deep-learning-based multi-view-imaging techniques to data from the H.E.S.S. Imaging Atmospheric Cherenkov Telescope array. We find that the earlier the fusion of layer information from…
The shower simulation code CORSIKA has been used to investigate the electron energy and angular distributions in high-energy showers. Based on the universality of both distributions, we develop an analytical description of Cherenkov light…
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).…
A new approach to simulate fluorescence photons produced in extensive air showers is described. A Monte Carlo program based on CORSIKA produces the fluorescence photons for each charged particle in the development of the shower. This method…
This paper proposes a frequent pattern data mining algorithm based on support vector machine (SVM), aiming to solve the performance bottleneck of traditional frequent pattern mining algorithms in high-dimensional and sparse data…
Current climate models often struggle with accuracy because they lack sufficient resolution, a limitation caused by computational constraints. This reduces the precision of weather forecasts and long-term climate predictions. To address…
Astrophysical sources of TeV gamma rays are usually established by Cherenkov telescope observations. These counting type instruments have a field of view of few degrees in diameter and record large numbers of particle air showers via their…
Very high energy gamma-ray astronomy based on the measurement of air shower particles at ground-level has only recently been established as a viable approach, complementing the well established air Cherenkov technique. This approach…
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,…
We studied the application of the Pseudo-Zernike features as image parameters (instead of the Hillas parameters) for the discrimination between the images produced by atmospheric electromagnetic showers caused by gamma-rays and the ones…
Machine learning is a useful tool for identifying radio pulses from cosmic-ray air showers and for cleaning such pulses from radio background. This can lower the detection threshold and increase the accuracy for the pulse time and…
Atmospheric Cerenkov telescopes are used to detect electromagnetic showers from primary gamma rays of energy ~300 GeV - ~10 TeV and to discriminate these from cascades due to hadrons using the Cerenkov images. The geomagnetic field affects…
We compared convolutional neural networks to the classical boosted decision trees for the separation of atmospheric particle showers generated by gamma rays from the particle-induced background. We conduct the comparison of the two…
Fluorescence telescopes are among the key instruments used for studying ultra-high energy cosmic rays in all modern experiments. We use model data for a small ground-based telescope EUSO-TA to try some methods of machine learning and neural…
We apply machine learning techniques in an attempt to predict and classify stellar properties from noisy and sparse time series data. We preprocessed over 94 GB of Kepler light curves from MAST to classify according to ten distinct physical…
The problem of development of the SVM classifier based on the modified particle swarm optimization has been considered. This algorithm carries out the simultaneous search of the kernel function type, values of the kernel function parameters…
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…
In this article, it is shown that the $C_k$ and $LCm$ variables, recently introduced as an effective way to discriminate gamma and proton-induced showers in large wide-field gamma-ray observatories, can be generalised to be used in arrays…