Abstract
The Baikal Gigaton Volume Detector (Baikal-GVD) is a km^3-scale neutrino detector currently under construction in Lake Baikal, Russia. The detector consists of several thousand optical sensors arranged on vertical strings, with 36 sensors per string. The strings are grouped into clusters of 8 strings each. Each cluster can operate as a stand-alone neutrino detector. The detector layout is optimized for the measurement of astrophysical neutrinos with energies of sim 100 TeV and above. Events resulting from charged current interactions of muon (anti-)neutrinos will have a track-like topology in Baikal-GVD. A fast chi ^2-based reconstruction algorithm has been developed to reconstruct such track-like events. The algorithm has been applied to data collected in 2019 from the first five operational clusters of Baikal-GVD, resulting in observations of both downgoing atmospheric muons and upgoing atmospheric neutrinos. This serves as an important milestone towards experimental validation of the Baikal-GVD design. The analysis is limited to single-cluster data, favoring nearly-vertical tracks.
Highlights
The Baikal Gigaton Volume Detector (Baikal-GVD) is a cubic-kilometer scale underwater neutrino detector currently under construction in Lake Baikal (Russia) at a location with a depth of 1366 m [1]
The detector elements are arranged along vertical strings which are in turn arranged in heptagonal clusters
Other track reconstruction algorithms are currently being developed for Baikal-GVD, which promise improvements in neutrino detection efficiency and angular resolution relative to the algorithm described here, albeit at the cost of higher CPU requirements
Summary
The Baikal Gigaton Volume Detector (Baikal-GVD) is a cubic-kilometer scale underwater neutrino detector currently under construction in Lake Baikal (Russia) at a location with a depth of 1366 m [1]. The algorithm has been optimized for the atmospheric neutrino detection Using this algorithm, a first analysis of muon tracks recorded by Baikal-GVD has been performed. The analysis of single-cluster events is independent of the intercluster time synchronization and calibration which themselves require dedicated cross checks and validation studies. It should be noted, that the single-cluster analysis has a limited angular coverage, favoring nearly-vertical tracks. The χ 2-based reconstruction algorithm is well suited for online data analysis thanks to its high speed It is currently integrated with the Baikal-GVD data processing system. Other track reconstruction algorithms are currently being developed for Baikal-GVD, which promise improvements in neutrino detection efficiency and angular resolution relative to the algorithm described here, albeit at the cost of higher CPU requirements.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
