Performance of the muon track reconstruction with the Baikal-GVD neutrino telescope
- NázevTitle
- Performance of the muon track reconstruction with the Baikal-GVD neutrino telescopePerformance of the muon track reconstruction with the Baikal-GVD neutrino telescope
- Druh výsledkuResult type
- Příspěvek ve sborníkuProceedings paper
- AutořiAuthors
- L. Fajt, I. Štekl, F. Šimkovic
- Časopis / citaceJournal / citation
- In: 37th International Cosmic Ray Conference. Trieste: Proceedings of Science, 2022. p. 1-9. ISSN 1824-8039.
- JazykLanguage
- eng
- ScopusScopus
- 2-s2.0-85120805007
- RIVRIV
- RIV/68407700:21670/21:00357072!RIV22-MSM-21670___
- ProjektProject
- Inženýrské aplikace fyziky mikrosvětaEngineering applications of microworld physics
AbstraktAbstract
Baikal-GVD is a km3 -scale neutrino telescope being constructed in Lake Baikal. Muon and partially tau (anti)neutrino interactions near the detector through the W± -boson exchange are accompanied by muon tracks. Reconstructed direction of the track is arguably the most precise probe of the neutrino direction attainable in Cerenkov neutrino telescopes. Muon reconstruction techniques adopted by Baikal-GVD are discussed in the present report. Performance of the muon reconstruction is studied using realistic Monte Carlo simulation of the detector. The algorithms are applied to real data from Baikal-GVD and the results are compared with simulations. The performance of the neutrino selection based on a boosted decision tree classifier is discussed.
Baikal-GVD is a km3 -scale neutrino telescope being constructed in Lake Baikal. Muon and partially tau (anti)neutrino interactions near the detector through the W± -boson exchange are accompanied by muon tracks. Reconstructed direction of the track is arguably the most precise probe of the neutrino direction attainable in Cerenkov neutrino telescopes. Muon reconstruction techniques adopted by Baikal-GVD are discussed in the present report. Performance of the muon reconstruction is studied using realistic Monte Carlo simulation of the detector. The algorithms are applied to real data from Baikal-GVD and the results are compared with simulations. The performance of the neutrino selection based on a boosted decision tree classifier is discussed.