A vertex reconstruction algorithm in the central detector of JUNO

TL;DR

This paper presents a vertex reconstruction algorithm for JUNO's central detector, utilizing maximum likelihood with PMT data to improve event localization in a large liquid scintillator setup.

Contribution

The paper introduces a novel vertex reconstruction algorithm that accounts for optical complexities, enhancing positional accuracy in JUNO's large-scale detector.

Findings

Improved vertex reconstruction accuracy demonstrated.

Algorithm effectively models optical processes in liquid scintillator.

Enhanced event localization for neutrino detection.

Abstract

The Jiangmen Underground Neutrino Observatory (JUNO) is designed to study neutrino mass hierarchy and measure three of the neutrino oscillation parameters with high precision using reactor antineutrinos. It is also able to study many other physical phenomena, including supernova neutrinos, solar neutrinos, geo-neutrinos, atmosphere neutrinos, and so forth. The central detector of JUNO contains 20,000~tons of liquid scintillator (LS) and about 18,000 20-inch photomultiplier tubes (PMTs), which is the largest liquid scintillator one under construction in the world up today. The energy resolution is expected to be 3\%/$\sqrt{E(MeV)}$. To meet the requirements of the experiment, an algorithm of vertex reconstruction, which takes into account time and charge information of PMTs, has been developed by deploying the maximum likelihood method and well understanding the complicated optical processes in the liquid scintillator.