Measuring muon tracks in Baikal-GVD using a fast reconstruction algorithm

TL;DR

This paper presents a fast reconstruction algorithm for muon tracks in Baikal-GVD, validated with 2019 data, enabling efficient detection of astrophysical neutrinos and atmospheric muons in Lake Baikal.

Contribution

A novel fast $$-based reconstruction algorithm for muon tracks in Baikal-GVD, applied to real data for the first time.

Findings

Successful reconstruction of atmospheric muons and neutrinos

Validation of detector performance with 2019 data

Demonstration of algorithm's efficiency for vertical tracks

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.