Related papers: Developing a Machine Learning Algorithm-Based Clas…
Very High Energy (VHE) gamma rays and charged cosmic rays (CCRs) provide an observational window into the acceleration mechanisms of extreme astrophysical environments. One of the major challenges at Imaging Air Cherenkov Telescopes (IACTs)…
The Cherenkov Telescope Array (CTA) will be the next-generation observatory in the field of very-high-energy (20 GeV to 300 TeV) gamma-ray astroparticle physics. Classically, data analysis in the field maximizes sensitivity by applying…
The Cherenkov Telescope Array (CTA) is the next generation facility of Imaging Atmospheric Cherenkov Telescopes. It will reach unprecedented sensitivity and energy resolution in very-high-energy gamma-ray astronomy. CTA will detect…
A new method for energy and mass composition estimation of primary cosmic ray radiation based on atmospheric Cerenkov light flux in extensive air showers (EAS) analysis is proposed. The Cerenkov light flux in EAS initiated by primary…
Arrays of imaging atmospheric Cherenkov telescopes (IACT) are superb instruments to probe the very-high-energy gamma-ray sky. This type of telescope focuses the Cherenkov light emitted from air showers, initiated by very-high-energy gamma…
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…
A methodology is proposed, which addresses the caveat that line-of-sight emission spectroscopy presents in that it cannot provide spatially resolved temperature measurements in nonhomogeneous temperature fields. The aim of this research is…
The Cherenkov Telescope Array (CTA) will be the next-generation observatory in the field of very-high-energy (20 GeV to 300 TeV) gamma-ray astroparticle physics. The traditional approach to data analysis in this field is to apply quality…
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…
Machine Learning algorithms are good tools for both classification and prediction purposes. These algorithms can further be used for scientific discoveries from the enormous data being collected in our era. We present ways of discovering…
Detecting cosmic gamma rays at high rates is the key to time-resolve the acceleration of particles within some of the most powerful events in the universe. Time-resolving the emission of gamma rays from merging celestial bodies, apparently…
The detection of very-high-energy gamma rays from supernova remnant shells testifies of the acceleration of particles at strong shocks. Many aspects of the particle acceleration remain however unclear. The study of individual objects is…
Accurate thermal analysis of composites and porous media requires detailed characterization of local thermal properties in small scale. For some important applications such as lithium-ion batteries, changes in the properties during the…
Machine Learning methods will play a fundamental role in our ability to optimize the science output from the next generation of large scale surveys. Given the peculiarities of astronomical data, it is crucial that algorithms are adapted to…
Large water Cherenkov detectors have shaped our current knowledge of neutrino physics and nucleon decay, and will continue to do so in the foreseeable future. These highly capable detectors allow for directional and topological, as well as…
Atmospheric Cerenkov telescopes are used to detect electromagnetic showers from primary gamma rays of energy > 300 GeV and to discriminate these from cascades due to hadrons using the shape and orientation of the Cerenkov images. The…
The imaging Cherenkov telescopes TAIGA-IACT, located in the Tunka valley of the republic Buryatia, accumulate a lot of data in a short period of time which must be efficiently and quickly analyzed. One of the methods of such analysis is the…
A simple 3D-reconstruction method for gamma-ray induced air showers is presented, which takes full advantage of the assets of a system of Atmospheric Cherenkov Telescopes combining stereoscopy and fine-grain imaging like the High Energy…
We present studies of quantum algorithms exploiting machine learning to classify events of interest from background events, one of the most representative machine learning applications in high-energy physics. We focus on variational quantum…
Subatomic particles can interact with target nuclei in matter or decay in flight, and an individual high-energy particle can induce a particle shower composed of numerous, lower-energy secondaries. These particle showers broadly exhibit…