Related papers: Optimizing the Wasserstein GAN for TeV Gamma Ray D…
In recent years, ground-based very-high-energy (VHE; E>100 GeV) gamma-ray astronomy has experienced a major breakthrough with the impressive astrophysical results obtained mainly by the current generation experiments like H.E.S.S., MAGIC,…
Generative adversarial nets (GANs) and variational auto-encoders have significantly improved our distribution modeling capabilities, showing promise for dataset augmentation, image-to-image translation and feature learning. However, to…
A new approach to Gamma/Hadron separation algorithms is proposed. The differences between Gamma and Hadron showers are notorious in two main aspects. The first is the wideness of the shower, and the second is the distribution of the angles…
The study of quantum generative models is well-motivated, not only because of its importance in quantum machine learning and quantum chemistry but also because of the perspective of its implementation on near-term quantum machines. Inspired…
Simulations of particle showers in calorimeters are computationally time-consuming, as they have to reproduce both energy depositions and their considerable fluctuations. A new approach to ultra-fast simulations are generative models where…
The Cherenkov Telescope Array (CTA) is planned to be the next generation ground based observatory for very high energy (VHE) gamma-ray astronomy. Gamma-rays provide a powerful insight into the non-thermal universe and hopefully a unique…
The HAWC observatory recently published their second source catalog with 39 very high energy gamma-ray sources based on 507 days of exposure time. Among these, there were 16 sources that are more than one degree away from any known TeV…
With the rapidly growing model complexity and data volume, training deep generative models (DGMs) for better performance has becoming an increasingly more important challenge. Previous research on this problem has mainly focused on…
Generative adversarial networks (GANs) are one of the most robust and versatile techniques in the field of generative artificial intelligence. In this work, we report on an application of GANs in the domain of synthetic spectral data…
Traditional generative adversarial networks (GAN) and many of its variants are trained by minimizing the KL or JS-divergence loss that measures how close the generated data distribution is from the true data distribution. A recent advance…
Indirect detection of gamma rays with ground-based observatories is currently the most sensitive experimental approach to characterize the gamma-ray sky at energies $>0.1$\,TeV. Ground-based detection of gamma-rays relies on the…
GAW, acronym for Gamma Air Watch, is a Research and Development experiment in the TeV range, whose main goal is to explore the feasibility of large field of view Imaging Atmospheric Cherenkov Telescopes. GAW is an array of three relatively…
The Fermi Gamma-ray Space Telescope regularly surveys the entire sky in the energy range between 0.3 and 100 GeV with an homogeneous coverage. This makes Fermi a very useful guide for ground-based Cherenkov-telescope arrays like VERITAS,…
Detecting changed regions in paired satellite images plays a key role in many remote sensing applications. The evolution of recent techniques could provide satellite images with very high spatial resolution (VHR) but made it challenging to…
The Atmospheric Cherenkov Imaging Technique has opened up the gamma-ray spectrumfrom 100 GeV to 50 TeV to astrophysical exploration. The development of the technique is described as are the basic principles underlying its use. The current…
Ground-based observations of Very High Energy (VHE) gamma rays from extreme astrophysical sources are significantly influenced by atmospheric conditions. This is due to the atmosphere being an integral part of the detector when utilizing…
VERITAS is a ground-based gamma-ray observatory that uses the imaging atmospheric Cherenkov technique and operates in the very high-energy (VHE) region of the gamma- ray spectrum from 100 GeV to 50 TeV. The observatory consists of an array…
The Cherenkov Telescope Array (CTA) will be the next generation ground based observatory in very high energy gamma ray astronomy. The facility will achieve a wide energy coverage, starting from a threshold of a few tens of GeV up to…
In real-life applications, certain images utilized are corrupted in which the image pixels are damaged or missing, which increases the complexity of computer vision tasks. In this paper, a deep learning architecture is proposed to deal with…
The VERITAS array of four 12-m imaging atmospheric-Cherenkov telescopes began full-scale operations in 2007, and is one of the world's most sensitive detectors of astrophysical VHE (E>100 GeV) $\gamma$-rays. Observations of active galactic…