Related papers: Event reconstruction for KM3NeT/ORCA using convolu…
We present a deep learning-based method for estimating the neutrino energy of charged-current neutrino-argon interactions. We employ a recurrent neural network (RNN) architecture for neutrino energy estimation in the MicroBooNE experiment,…
The Cherenkov Telescope Array is the next generation of observatory using imaging air Cherenkov technique for very-high-energy gamma-ray astronomy. Its first prototype telescope is operational on-site at La Palma and its data acquisitions…
Deep Convolutional Neural Networks (DCNN) have been proven to be effective for various computer vision problems. In this work, we demonstrate its effectiveness on a continuous object orientation estimation task, which requires prediction of…
Traditional microlensing event vetting methods require highly trained human experts, and the process is both complex and time-consuming. This reliance on manual inspection often leads to inefficiencies and constrains the ability to scale…
The ANTARES Collaboration has completed in 2008 the deployment of what is currently the largest high energy neutrino detector in the Northern hemisphere. The search for cosmic neutrinos in the energy range between tens of GeV and tens of…
The observation of high-energy extraterrestrial neutrinos is one of the most promising future options to increase our knowledge on non-thermal processes in the universe. Neutrinos are e.g. unavoidably produced in environments where…
We develop a first-principles formalism, based on the transport equation in the line-of-sight approximation, to link the expected number of muons at neutrino telescopes to the flux of neutrinos at the Earth's surface. We compute the…
Liquid Argon Time Projection Chamber (LArTPC) detector technology offers a wealth of high-resolution information on particle interactions, and leveraging that information to its full potential requires sophisticated automated reconstruction…
Hyper-Kamiokande (Hyper-K) is a next-generation long baseline neutrino experiment. One of its primary physics goals is to measure neutrino oscillation parameters precisely, including the Dirac CP violating phase. As conventional $\nu_{\mu}$…
Detecting extreme events in large datasets is a major challenge in climate science research. Current algorithms for extreme event detection are build upon human expertise in defining events based on subjective thresholds of relevant…
Based on the DUSTGRAIN-pathfinder suite of simulations, we investigate observational degeneracies between nine models of modified gravity and massive neutrinos. Three types of machine learning techniques are tested for their ability to…
HAWC is a ground-based observatory consisting of 300 water Cherenkov detectors, which observes the extensive air showers induced by cosmic rays from some TeV to a few PeV and, in particular, gamma rays from 300 GeV to more than 100 TeV. One…
Extensive air showers created by high-energy particles interacting with the Earth atmosphere can be detected using imaging atmospheric Cherenkov telescopes (IACTs). The IACT images can be analyzed to distinguish between the events caused by…
To complement the IceCube neutrino telescope currently under construction at the South Pole, the three Mediterranean neutrino telescope projects ANTARES, NEMO and NESTOR have joined forces to develop, construct and operate a km^3-scale…
The Booster Neutrino Experiment (MiniBooNE) searches for muon neutrino to electron neutrino oscillations using the ~1 GeV neutrino beam produced by the FNAL Booster synchrotron. The array of photomultiplier tubes (PMTs) lining the MiniBooNE…
The energy--zenith angular event distribution in a neutrino telescope provides a unique tool to determine at the same time the neutrino-nucleon cross section at extreme kinematical regions, and the high energy neutrino flux. By using a…
We present a deep learning approach for vertex reconstruction of neutrino-nucleus interaction events, a problem in the domain of high energy physics. In this approach, we combine both energy and timing data that are collected in the MINERvA…
Convolutional neural networks (CNNs) are widely used state-of-the-art computer vision tools that are becoming increasingly popular in high energy physics. In this paper, we attempt to understand the potential of CNNs for event…
The planned Cherenkov Telescope Array (CTA) is a future observatory for very-high-energy (VHE) gamma-ray astronomy composed of one site per hemisphere. It aims at 10 times better sensitivity, a better angular resolution and wider energy…
The Deep Underground Neutrino Experiment is a next-generation neutrino oscillation experiment that aims to measure $CP$-violation in the neutrino sector as part of a wider physics program. A deep learning approach based on a convolutional…