Related papers: Particle identification in ground-based gamma-ray …

Ground-based gamma-ray astronomy experienced a major boost with the advent of the present generation of Imaging Atmospheric Cherenkov Telescopes (IACTs) in the past decade. Photons of energies >~ 0.1 TeV are a very useful tool in the study…

The next generation of observatories will facilitate the discovery of new types of astrophysical transients. The detection of such phenomena, whose characteristics are presently poorly constrained, will hinge on the ability to perform blind…

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…

In gamma ray astronomy with Cherenkov telescopes, machine learning models are needed to guess what kind of particles generated the detected light, and their energies and directions. The focus in this work is on the classification task,…

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…

Imaging Cherenkov detectors are largely used in modern nuclear and particle physics experiments where cutting-edge solutions are needed to face always more growing computing demands. This is a fertile ground for AI-based approaches and at…

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,…

Telescopes -- far seeing -- have since centuries revealed insights to objects at cosmic distances. Adopted for gamma-ray-astronomy, ground based Cherenkov-telescopes image the faint Cherenkov-light of air-showers induced by cosmic…

Gamma-ray photons can convert into axion-like particles (ALPs) and vice versa when interacting with astrophysical magnetic fields. The conversions of ALPs may have important implications for astrophysics since they would imprint…

With the great promise of deep learning, discoveries of new particles at the Large Hadron Collider (LHC) may be imminent. Following the discovery of a new Beyond the Standard model particle in an all-hadronic channel, deep learning can also…

During the last two decades Gamma-Ray Astronomy has emerged as a powerful tool to study cosmic ray physics. In fact, photons are not deviated by galactic or extragalactic magnetic fields so their directions bring the information of the…

Deep learning algorithms offer a powerful means to automatically analyze the content of medical images. However, many biological samples of interest are primarily transparent to visible light and contain features that are difficult to…

The Cherenkov Telescope Array (CTA) will be the next generation of ground based gamma-ray telescopes allowing us to study very high energy phenomena in the Universe. CTA aims to gain about a factor of ten in sensitivity compared to current…

With the development of the Imaging Atmospheric Cherenkov Technique (IACT), Gamma-ray astronomy has become one of the most interesting and productive fields of astrophysics. Current IACT telescope arrays (MAGIC, H.E.S.S, VERITAS) use…

Gamma-ray astronomy from hundreds of GeV to PeV is confined to ground-based experiments that detect air showers induced by $\gamma$-rays entering Earth's atmosphere. While particle detector arrays feature huge detection areas, accurately…

We consider a machine learning algorithm to detect and identify strong gravitational lenses on sky images. First, we simulate different artificial but very close to reality images of galaxies, stars and strong lenses, using six different…

The last 20 years have seen the development of new techniques in Astroparticle Physics providing access to the highest end of the electromagnetic spectrum. It has been shown that some sources emit photons up to energies close to 100 TeV.…

As we enter the era of large-scale imaging surveys with the up-coming telescopes such as LSST and SKA, it is envisaged that the number of known strong gravitational lensing systems will increase dramatically. However, these events are still…

The success of Convolutional Neural Networks (CNNs) in image classification has prompted efforts to study their use for classifying image data obtained in Particle Physics experiments. Here, we discuss our efforts to apply CNNs to 2D and 3D…

A Convolutional Neural Network architecture was used to classify various isotopes of time-sequenced gamma-ray spectra, a typical output of a radiation detection system of a type commonly fielded for security or environmental measurement…