Deep Neural Networks for combined neutrino energy estimate with KM3NeT/ORCA6
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21670%2F24%3A00381651" target="_blank" >RIV/68407700:21670/24:00381651 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.22323/1.444.1035" target="_blank" >https://doi.org/10.22323/1.444.1035</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.22323/1.444.1035" target="_blank" >10.22323/1.444.1035</a>
Alternative languages
Result language
angličtina
Original language name
Deep Neural Networks for combined neutrino energy estimate with KM3NeT/ORCA6
Original language description
KM3NeT/ORCA is a large-volume water-Cherenkov neutrino detector, currently under construction at the bottom of the Mediterranean Sea at a depth of 2450 meters. The main research goal of ORCA is the measurement of the neutrino mass ordering and the atmospheric neutrino oscillation parameters. Additionally, the detector is also sensitive to a wide variety of phenomena including non-standard neutrino interactions, sterile neutrinos, and neutrino decay. This contribution describes the use of a machine learning framework for building Deep Neural Networks (DNN) which combine multiple energy estimates to generate a more precise reconstructed neutrino energy. The model is optimized to improve the oscillation analysis based on a data sample of 433 kton-years of KM3NeT/ORCA with 6 detection units. The performance of the model is evaluated by determining the sensitivity to oscillation parameters in comparison with the standard energy reconstruction method of maximizing a likelihood function. The results show that the DNN is able to provide a better energy estimate with lower bias in the context of oscillation analyses.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10308 - Astronomy (including astrophysics,space science)
Result continuities
Project
<a href="/en/project/LM2023063" target="_blank" >LM2023063: Laboratoire Souterrain de Modane – participation of the Czech Republic</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
38th International Cosmic Ray Conference
ISBN
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ISSN
1824-8039
e-ISSN
1824-8039
Number of pages
10
Pages from-to
1-10
Publisher name
SISSA-The International School for Advanced Studies
Place of publication
Trieste
Event location
Nagoya
Event date
Jul 26, 2023
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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