Related papers: Analysis of Fluorescence Telescope Data Using Mach…
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…
EUSO--TA is a ground-based telescope installed in 2013 in the Black Rock Mesa Telescope Array (BRM-TA) site, operating with 2.5$\mu$s time resolution to observe the night sky in the UV range. The optical system contains two 1m$^2$ Fresnel…
The use of machine learning techniques has significantly increased the physics discovery potential of neutrino telescopes. In the upcoming years, we are expecting upgrade of currently existing detectors and new telescopes with novel…
The experimental technique of fluorescence light observation is used in current and planned air shower experiments that aim at understanding the origin of ultra-high energy cosmic rays. In the fluorescence technique, the geometry of the…
Large-scale photometric surveys are revolutionizing astronomy by delivering unprecedented amounts of data. The rich data sets from missions such as the NASA Kepler and TESS satellites, and the upcoming ESA PLATO mission, are a treasure…
The EUSO (Extreme Universe Space Observatory) project is developing a new mission concept for the scientific research of Ultra High Energy Cosmic Rays (UHECRs) from space. The EUSO wide-field telescope will look down from space onto the…
The Fluorescence Telescope is one of the two telescopes on board the Extreme Universe Space Observatory on a Super Pressure Balloon II (EUSO-SPB2). EUSO-SPB2 is an ultra-long-duration balloon mission that aims at the detection of Ultra High…
An array of large observational programs using ground-based and space-borne telescopes is planned in the next decade. The forthcoming wide-field sky surveys are expected to deliver a sheer volume of data exceeding an exabyte. Processing the…
Along the years HiRes and AGASA experiments have explored the fluorescence and the ground array experimental techniques to measure extensive air showers, being both essential to investigate the ultra-high energy cosmic rays. However, such…
The field of UHECRs (Ultra-High energy cosmic Rays) and the understanding of particle acceleration in the cosmos, as a key ingredient to the behaviour of the most powerful sources in the universe, is of outmost importance for astroparticle…
Astronomy has entered the big data era and Machine Learning based methods have found widespread use in a large variety of astronomical applications. This is demonstrated by the recent huge increase in the number of publications making use…
The fluorescence technique has been successfully used to detect ultrahigh energy cosmic rays by indirect measurements. The underlying idea is that the number of charged particles in the atmospheric shower, i.e, its longitudinal profile, can…
Machine learning is a field that has been growing in importance since the early 2010s due to the increasing accuracy of classification models and hardware advances that have enabled faster training on large datasets. In the field of…
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…
The Extreme Universe Space Observatory-Telescope Array (EUSO-TA) is a ground-based experiment, part of the JEM-EUSO (Joint Experiment Missions -- Extreme Universe Space Observatory) dedicated to the observation of Ultra High Energy Cosmic…
To maximize the accuracy of background simulation and event reconstruction, high-energy neutrino telescopes require detailed knowledge of light propagation over a large volume of detection medium. If light scattering and absorption leng ths…
The JEM-EUSO Collaboration aims at studying Ultra High Energy Cosmic Rays (UHECR) from space. To reach this goal, a series of pathfinder missions has been developed to prove the observation principle and to raise the technological readiness…
Machine learning techniques in neutrino physics have traditionally relied on simulated data, which provides access to ground-truth labels. However, the accuracy of these simulations and the discrepancies between simulated and real data…
With the volume and availability of astronomical data growing rapidly, astronomers will soon rely on the use of machine learning algorithms in their daily work. This proceeding aims to give an overview of what machine learning is and delve…
We use the CORSIKA air shower simulation program to review the method for assigning energies to ultra-high energy (UHE) cosmic rays viewed with the air fluorescence technique. This technique uses the atmosphere as a calorimeter, and we…