An efficient hit finding algorithm for Baikal-GVD muon reconstruction

TL;DR

This paper introduces an efficient algorithm for muon event reconstruction in the Baikal-GVD neutrino telescope, effectively distinguishing Cherenkov light signals from noise hits using a graph-based clique method.

Contribution

The paper presents a novel clique-based algorithm leveraging directional causality to improve signal extraction in muon reconstruction for large-scale neutrino detectors.

Findings

Achieves over 90% retention of true Cherenkov signal hits.

Successfully distinguishes signal from noise in realistic Monte Carlo simulations.

Applicable across a wide range of muon energies.

Abstract

The Baikal-GVD is a large scale neutrino telescope being constructed in Lake Baikal. The majority of signal detected by the telescope are noise hits, caused primarily by the luminescence of the Baikal water. Separating noise hits from the hits produced by Cherenkov light emitted from the muon track is a challenging part of the muon event reconstruction. We present an algorithm that utilizes a known directional hit causality criterion to contruct a graph of hits and then use a clique-based technique to select the subset of signal hits.The algorithm was tested on realistic detector Monte-Carlo simulation for a wide range of muon energies and has proved to select a pure sample of PMT hits from Cherenkov photons while retaining above 90\% of original signal.