Related papers: Deep Learning Based Event Reconstruction for the I…
Supernovae represent some of the most energetically explosive events in the universe, with a substantial fraction of their released gravitational energy carried away by neutrinos. This study evaluates the sensitivity of three…
The IceCube Neutrino Observatory is a cubic-kilometer high-energy neutrino detector deployed in the Antarctic ice. Two major event classes are charged-current electron and muon neutrino interactions. In this contribution, we discuss the…
IceCube-Gen2, the next generation of the IceCube Neutrino Observatory at the South Pole, will consist of three co-located arrays: a deep Optical Array and a more shallow and larger Radio Array for neutrino detection in the ice, and a…
The IceCube Neutrino Observatory is highly sensitive to neutrino bursts of $\mathcal{O}$(10) MeV energy that are would be generated by core collapse supernovae in our Galaxy. It will resolve temporal structures in supernova light curves…
Tasks involving the analysis of geometric (graph- and manifold-structured) data have recently gained prominence in the machine learning community, giving birth to a rapidly developing field of geometric deep learning. In this work, we…
Ultra-high-energy (UHE) neutrinos are unique cosmic messengers that can traverse cosmological distances unattenuated, offering direct insight into the most energetic processes in the universe. Radio detection promises significant advantages…
In neutrino experiments, neutrino energy reconstruction is crucial because neutrino oscillations and differential cross-sections are functions of neutrino energy. It is also challenging due to the complexity in the detector response and…
The field of deep learning has become increasingly important for particle physics experiments, yielding a multitude of advances, predominantly in event classification and reconstruction tasks. Many of these applications have been adopted…
The reconstruction of neutrino events in the IceCube experiment is crucial for many scientific analyses, including searches for cosmic neutrino sources. The Kaggle competition "IceCube -- Neutrinos in Deep ice" was a public machine learning…
Next-generation ultra-high-energy (UHE) neutrino telescopes, presently under planning, will have the potential to probe the decay of heavy dark matter (DM) into UHE neutrinos, with energies in excess of $10^7$~GeV. Yet, this potential may…
We introduce a method to reconstruct the kinematics of neutral-current deep inelastic scattering (DIS) using a deep neural network (DNN). Unlike traditional methods, it exploits the full kinematic information of both the scattered electron…
To date, accelerator neutrino experiments have had only limited success including neutrons in the neutrino event reconstruction event by event. Produced neutrons often interact in a detector leaving an energy deposition that does not…
High-energy neutrino telescopes such as IceCube or KM3NeT issue public alerts describing the characteristics of possible astrophysical high-energy neutrino events. This information, particularly with respect to the arrival direction and the…
The IceCube Neutrino Observatory is currently the largest and most sensitive detector for astrophysical neutrinos and has pioneered the field of high-energy neutrino astronomy. Despite being designed with the primary goal of identifying…
Using advanced machine learning techniques, we developed a method for reconstructing precisely the arrival direction and energy of ultra-high-energy cosmic rays from the voltage traces they induced on ground-based radio detector arrays. In…
The initial evidence of astrophysical neutrinos by the IceCube Neutrino Observatory stemmed from the high-energy starting events (HESE) sample: a selection of the highest-energy neutrino interactions that occurred within the detector…
The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino detector off the French coast will instrument several megatons of seawater with…
Binary neutron star (BNS) mergers can be sources of ultrahigh-energy (UHE) cosmic rays and potential emitters of UHE neutrinos. The upcoming and current radio neutrino detectors like the Giant Radio Array for Neutrino Detection (GRAND),…
The directionality information of incoming neutrinos is essential to atmospheric neutrino oscillation analysis since it is directly related to the oscillation baseline length. Large homogeneous liquid scintillator detectors, while offering…
Astrophysical neutrinos at $\sim$EeV energies promise to be an interesting source for astrophysics and particle physics. Detecting the predicted cosmogenic (``GZK'') neutrinos at 10$^{16}$ - 10$^{20}$ eV would test models of cosmic ray…