Cosmic-ray detection with and novel reconstructionalgorithms for the ARIANNA experiment
36th International Cosmic Ray Conference, ICRC2019, Madison, Wisconsin, USA, 24 Jul 2019 - 1 Aug 2019; PoS 366 (2019). : The ARIANNA experiment in Antarctica is targeted at detecting the radio emission of neutrinointeractions in the ice. However, due to their antennas being deployed close to the sur...
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ftdatacite:10.3204/pubdb-2020-00374 2023-05-15T13:39:51+02:00 Cosmic-ray detection with and novel reconstructionalgorithms for the ARIANNA experiment Nelles, Anna Friederike 2019 https://dx.doi.org/10.3204/pubdb-2020-00374 http://bib-pubdb1.desy.de/record/434831 en eng Deutsches Elektronen-Synchrotron, DESY, Hamburg Conference Paper Text article-journal ScholarlyArticle 2019 ftdatacite https://doi.org/10.3204/pubdb-2020-00374 2021-11-05T12:55:41Z 36th International Cosmic Ray Conference, ICRC2019, Madison, Wisconsin, USA, 24 Jul 2019 - 1 Aug 2019; PoS 366 (2019). : The ARIANNA experiment in Antarctica is targeted at detecting the radio emission of neutrinointeractions in the ice. However, due to their antennas being deployed close to the surface, ARIANNAstations have routinely been used for cosmic ray detection. These fully self-triggeredevents have in-turn been used to improve reconstruction algorithms and to provide a proof-ofprinciplefor neutrino detection and reconstruction. We will present the detected events and theircharacteristics. Also, we will elaborate on novel algorithms to reconstruct the cosmic-ray energyfrom a single station and to reconstruct the signal polarization from distributed antennas. Whilenecessary for sparse neutrino arrays, these methods also provide new opportunities for stand-alonecosmic ray arrays to improve event statistics and reconstruction quality. Conference Object Antarc* Antarctica DataCite Metadata Store (German National Library of Science and Technology) |
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English |
description |
36th International Cosmic Ray Conference, ICRC2019, Madison, Wisconsin, USA, 24 Jul 2019 - 1 Aug 2019; PoS 366 (2019). : The ARIANNA experiment in Antarctica is targeted at detecting the radio emission of neutrinointeractions in the ice. However, due to their antennas being deployed close to the surface, ARIANNAstations have routinely been used for cosmic ray detection. These fully self-triggeredevents have in-turn been used to improve reconstruction algorithms and to provide a proof-ofprinciplefor neutrino detection and reconstruction. We will present the detected events and theircharacteristics. Also, we will elaborate on novel algorithms to reconstruct the cosmic-ray energyfrom a single station and to reconstruct the signal polarization from distributed antennas. Whilenecessary for sparse neutrino arrays, these methods also provide new opportunities for stand-alonecosmic ray arrays to improve event statistics and reconstruction quality. |
format |
Conference Object |
author |
Nelles, Anna Friederike |
spellingShingle |
Nelles, Anna Friederike Cosmic-ray detection with and novel reconstructionalgorithms for the ARIANNA experiment |
author_facet |
Nelles, Anna Friederike |
author_sort |
Nelles, Anna Friederike |
title |
Cosmic-ray detection with and novel reconstructionalgorithms for the ARIANNA experiment |
title_short |
Cosmic-ray detection with and novel reconstructionalgorithms for the ARIANNA experiment |
title_full |
Cosmic-ray detection with and novel reconstructionalgorithms for the ARIANNA experiment |
title_fullStr |
Cosmic-ray detection with and novel reconstructionalgorithms for the ARIANNA experiment |
title_full_unstemmed |
Cosmic-ray detection with and novel reconstructionalgorithms for the ARIANNA experiment |
title_sort |
cosmic-ray detection with and novel reconstructionalgorithms for the arianna experiment |
publisher |
Deutsches Elektronen-Synchrotron, DESY, Hamburg |
publishDate |
2019 |
url |
https://dx.doi.org/10.3204/pubdb-2020-00374 http://bib-pubdb1.desy.de/record/434831 |
genre |
Antarc* Antarctica |
genre_facet |
Antarc* Antarctica |
op_doi |
https://doi.org/10.3204/pubdb-2020-00374 |
_version_ |
1766125523628457984 |