Abstract
The Radio Neutrino Observatory in Greenland (RNO-G) is a radio-based ultra-high energy neutrino detector located at Summit Station, Greenland. It is still being constructed, with 7 stations currently operational. Neutrino detection works by measuring Askaryan radiation produced by neutrino-nucleon interactions. A neutrino candidate must be found amidst other backgrounds which are recorded at much higher rates—including cosmic-rays and anthropogenic noise—the origins of which are sometimes unknown. Here we describe a method to classify different noise classes using the latent space of a variational autoencoder. The latent space forms a compact representation that makes classification tractable. We analyze data from a noisy and a silent station. The method automatically detects and allows us to qualitatively separate multiple event classes, including physical wind-induced signals, for both the noisy and the quiet station.
Original language | English (US) |
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Article number | 1056 |
Journal | Proceedings of Science |
Volume | 444 |
State | Published - Sep 27 2024 |
Event | 38th International Cosmic Ray Conference, ICRC 2023 - Nagoya, Japan Duration: Jul 26 2023 → Aug 3 2023 |
All Science Journal Classification (ASJC) codes
- General