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Studies of the influence of different hadronic models on extensive air showers at ultra-high energies are presented. The hadronic models considered are those implemented in the well-known QGSJET and SIBYLL event generators. The different…
The energy spectrum of muons at ground level in air showers are studied and a new observable is proposed to constrain hadronic interaction models used in air shower simulations. An asymmetric Gaussian function is proposed to describe the…
The Cherenkov light produced in air showers largely contributes to the signal observed in ground-based gamma-ray and cosmic-ray observatories. Yet, no description of this phenomenon is available covering both regions of small and large…
Deep neural networks are a powerful technique that have found ample applications in several branches of Physics. In this work, we apply machine learning algorithms to a specific problem of Cosmic Ray Physics: the estimation of the muon…
Pool fires are canonical representations of many accidental fires, which can exhibit an unstable unsteady behaviour, known as puffing, which involves a strong coupling between the temperature and velocity fields. Despite their practical…
In the atmospheric Cerenkov technique gamma rays are detected against the abundant background produced by hadronic showers. In order to improve the signal to noise ratio of the experiment, it is necessary to reject a significant fraction of…
We propose a novel deep fusion architecture, CaloriNet, for the online estimation of energy expenditure for free living monitoring in private environments, where RGB data is discarded and replaced by silhouettes. Our fused convolutional…
We present the study of a fuzzy clustering algorithm for the Belle II electromagnetic calorimeter using Graph Neural Networks. We use a realistic detector simulation including simulated beam backgrounds and focus on the reconstruction of…
A small prototype of a finely granulated digital hadron calorimeter with Resistive Plate Chambers as active elements was exposed to positrons of 1 . 16 GeV energy from the Fermilab test beam. The response function, energy resolution, as…
The properties of cosmic rays with energies above 10**6 GeV have to be deduced from the spacetime structure and particle content of the air showers which they initiate. In this review we summarize the phenomenology of these giant air…
We present results on the reconstruction of electromagnetic (EM) activity from photons produced in charged current $\nu_{\mu}$ interactions with final state $\pi^0$s. We employ a fully-automated reconstruction chain capable of identifying…
High-energy cosmic rays are observed indirectly by detecting the extensive air showers initiated in Earth's atmosphere. The interpretation of experimental data relies on accurate modeling of the air shower development. Simulations based on…
Power management is an expensive and important issue for large computational infrastructures such as datacenters, large clusters, and computational grids. However, measuring energy consumption of scalable systems may be impractical due to…
Accurate clustering of electromagnetic energy deposits is essential for reconstructing photons and electrons in modern hadron collider experiments, where boosted topologies and pileup cause overlapping showers and ambiguous energy…
Data from multiple experiments suggest that the current interaction models used in Monte Carlo simulations do not correctly reproduce the hadronic interactions in air showers produced by ultra-high-energy cosmic rays (UHECR). We have…
CALICE collaboration is developing highly granular calorimeters suitable for individual reconstruction of particles in the jets using Particle Flow Algorithms. Such calorimeters should provide the best jet energy resolution at future high…
In High Energy Physics experiments Particle Flow (PFlow) algorithms are designed to provide an optimal reconstruction of the nature and kinematic properties of the particles produced within the detector acceptance during collisions. At the…
Artificial intelligence deployment for automated photovoltaic (PV) monitoring faces interpretability barriers that limit adoption in energy infrastructure applications. While deep learning achieves high accuracy in thermal fault detection,…
The Belle~II electromagnetic calorimeter consists of 8376 CsI(Tl) scintillation crystals and is not only used for measuring electromagnetic particles but also for identifying and determining the position of hadrons, particularly…
Experiments in superfluid 4He show that at low temperatures, energy dissipation from moving vortices is many orders of magnitude larger than expected from mutual friction. Here we investigate other mechanisms for energy loss by a…