Year: 2025
Type: conference-paper
Abstract: Ultra-high-energy neutrinos are an invaluable messenger for learning about the most energetic and distant astrophysical processes in the universe. Detecting them is challenging due to their extremely low flux and small cross section, necessitating immense detection volumes. The Radio Neutrino Observatory in Greenland (RNO-G) addresses this challenge by leveraging the Askaryan effect, using sparse radio instrumentation to detect neutrino-induced cascades in ice. However, cosmic rays represent an important background, as their induced showers produce radio emission that can mimic neutrino signals; both in-air emission, primarily through the geomagnetic effect, and in-ice Askaryan emission can act as backgrounds for a neutrino search. At the same time, these radio emissions from cosmic-ray induced air showers provide a crucial tool for detector calibration and validation. This work presents progress toward quantifying and separating these backgrounds in RNO-G’s deep antennas using machine learning classification methods.
DOI: 10.22323/1.501.1057
Authors: Bryan L. Hendricks, Sanyukta Agarwal, Juan Antonio Aguilar, Nathaniel Alden, Shoukat Ali, Patrick Allison, Michael Betts, Dave Besson, Abigail Bishop, Olga Botner, Sjoerd Bouma, Stijn Buitink, Ruben Camphyn, Jason Chan, Simon Chiche, Brian Clark, Alan Coleman, Kenneth Couberly, Simon De Kockere, Krijn de Vries, Cosmin Deaconu, Pawan Giri, Christian Glaser, Thorsten Glüsenkamp, Heidi Gui, Allan Hallgren, Steffen Hallmann, Jordan Hanson, Klaus Helbing, Jakob Henrichs, Nils Heyer, Christian Hornhuber, Enrique Huesca Santiago, Kaeli Hughes, Annanay Jaitly, Timo Karg, Albrecht Karle, John Kelley, Claudio Kopper, michael Korntheuer, Marek Kowalski, Ilya Kravchenko, Ryan Krebs, Mirko Kugelmeier, Robert Lahmann, Martin Liu, Mathew Marsee, Katharine Mulrey, Marco Muzio, Anna Nelles, Alexander Novikov, Alisa Nozdrina, Eric Oberla, Bob Oeyen, Noppadol Punsuebsay, Lilly Pyras, Martin Langgård Ravn, Adam Rifaie, Dirk Ryckbosch, Felix Schlüter, Olaf Scholten, Dave Seckel, Mohammad Seikh, Zeynep Su Selcuk, Juliana Stachurska, Jethro Stoffels, Simona Toscano, Delia Tosi, James Tutt, Dieder Jan Van Den Broeck, Nick van Eijndhoven, Abigail G. Vieregg, Aishwarya Vijai, Christoph Welling, Dawn Williams, Philipp Windischhofer, Stephanie Wissel, Rob Young, Adrian Zink
Institution: Pennsylvania State University
Language: English
Subfield: Nuclear and High Energy Physics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: hybrid
Awards: Infrastructure to enhance IceCube, G1876581842, Collaborative Research: WoU-MMA: New Advancements to Enable Multi-Messenger Neutrino Astrophysics with the Radio Neutrino Observatory in Greenland, RII Track-2 FEC: The IceCube EPSCoR Initiative (IEI) - IceCube and the Data Revolution, G434337789, G6461067166, Reconstruction of the properties of ultra-high energy neutrinos from radio detector data using deep learning, Collaborative Research: WoU-MMA: Ultrahigh Energy Neutrinos with the Radio Neutrino Observatory in Greenland, Collaborative Research: WoU-MMA: New Advances to Enable Multi-Messenger Neutrino Astrophysics with the Radio Neutrino Observatory in Greenland, Collaborative Research: WoU-MMA: Ultrahigh Energy Neutrinos with the Radio Neutrino Observatory in Greenland, Collaborative Research: WoU-MMA: New Advancements to Enable Multi-Messenger Neutrino Astrophysics with the Radio Neutrino Observatory in Greenland, Discovering neutrinos of extreme energies with the Radio Neutrino Observatory Greenland, WoU-MMA: Cosmic Ray and Background Identification with RNO-G
OpenAlex ID: W4414480304
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