Related papers: Machine Learning Approach for Air Shower Recogniti…

The Shower Deconstruction methodology is pivotal in distinguishing signal and background jets, leveraging the detailed information from perturbative parton showers. Rooted in the Neyman-Pearson lemma, this method is theoretically designed…

In order to allow machine learning algorithms to extract knowledge from raw data, these data must first be cleaned, transformed, and put into machine-appropriate form. These often very time-consuming phase is referred to as preprocessing.…

The most important goal of studying an extensive air shower is to find the energy, mass and arrival direction of its primary cosmic ray. In order to find these parameters, the core position and arrival direction of the shower should be…

We present the data acquisition and control software for the operation of the Mini-Extreme Universe Space Observatory (EUSO), a space-based fluorescence telescope for the observation of extensive air showers and atmospheric phenomena. This…

This paper presents the development of a new entropy-based feature selection method for identifying and quantifying impacts. Here, impacts are defined as statistically significant differences in spatio-temporal fields when comparing…

Machine learning models play a vital role in the prediction task in several fields of study. In this work, we utilize the ability of machine learning algorithms to predict the occurrence of extreme events in a nonlinear mechanical system.…

The next generation of ultra-high energy cosmic ray (UHECR) and very-high energy neutrino observatories will address the challenge of the extremely low fluxes of these particles at the highest energies. EUSO-SPB2 (Extreme Universe Space…

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…

Recently, several normalizing flow-based deep generative models have been proposed to accelerate the simulation of calorimeter showers. Using CaloFlow as an example, we show that these models can simultaneously perform unsupervised anomaly…

This study explores the application of autoencoder-based machine learning techniques for anomaly detection to identify exoplanet atmospheres with unconventional chemical signatures using a low-dimensional data representation. We use the…

Issues relating to extensive air showers observation by a space-borne fluorescence detector and the effects of clouds on the observations are investigated using Monte Carlo simulation. The simulations assume the presence of clouds with…

The need of real-time of monitoring and alerting systems for Space Weather hazards has grown significantly in the last two decades. One of the most important challenge for space mission operations and planning is the prediction of solar…

The Extreme Universe Space Observatory - Super Pressure Balloon (EUSO-SPB2) mission will fly two custom telescopes that feature Schmidt optics to measure \v{C}erenkov- and fluorescence-emission of extensive air-showers from cosmic rays at…

Results will be shown from the ASTRONEU array developed and operated in the outskirts of Patras, Greece. An array of 9 scintillator detectors and 3 antennas were deployed to study Extensive Air Showers (EAS) as a tool for calibrating an…

EUSO-SPB2 is a second generation Extreme Universe Space Observatory (EUSO) on a Super-Pressure Balloon (SPB). This document describes the physics capabilities, the proposed technical design of the instruments, and the simulation and…

Atmospheric neutrino oscillations are important to the study of neutrino properties, including the neutrino mass ordering problem. A good capability to identify neutrinos' flavor and neutrinos against antineutrinos is crucial in such…

We report on the design and the expected performance of a low cost hybrid detection system suitable for operation as an autonomous unit in strong electromagnetic noise environments. The system consists of three particle detectors…

The Giant Radio Array for Neutrino Detection (GRAND) aims to detect radio signals from extensive air showers (EAS) caused by ultra-high-energy (UHE) cosmic particles. Galactic, hardware-like, and anthropogenic noise are expected to…

Space weather events may cause damage to several fields, including aviation, satellites, oil and gas industries, and electrical systems, leading to economic and commercial losses. Solar flares are one of the most significant events, and…

We present a full model of surface-detector responses to extensive air showers. The model is motivated by the principles of air-shower universality and can be applied to different types of surface detectors. Here we describe a…