Speaker
Description
The Jiangmen Underground Neutrino Observatory (JUNO) is a next-generation neutrino experiment in south China currently in the commissioning stage. JUNO’s primary objective is to determine the neutrino mass ordering (NMO) mainly by detecting reactor antineutrinos.
Unlike typical accelerator experiments, the JUNO experiment typically detects physical events (such as the inverse beta decay of reactor antineutrinos) that generate multiple trigger signals correlated in time. This feature has caused extra complexity when designing its offline data processing software, especially when time-correlated analysis plays a vital role analyzing JUNO data.
This contribution will briefly introduce the design of the JUNO offline software (JUNOSW) that implements the offline data processing and MC simulation of JUNO. In particular, we will introduce JUNOSW's event data model (EDM) based on TObject that comprehensively correlates event objects by implementing a smart pointer using ROOT's TProcessID mechanism.