Study Data from Shandong University Update Knowledge of Machine Learning (A mult i-purpose reconstruction method based on machine learning for atmospheric neutri nos at JUNO)
Study Data from Shandong University Update Knowledge of Machine Learning (A mult i-purpose reconstruction method based on machine learning for atmospheric neutri nos at JUNO)
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Researchers detail new data in artificial intelli gence. According to news originating from Shandong University by NewsRx editors, the research stated, “The Jiangmen Underground Neutrino Observatory (JUNO) expe riment is designed to measure the neutrino mass ordering (NMO) using a 20-kton l iquid scintillator (LS) detector.” Our news reporters obtained a quote from the research from Shandong University: “Besides the precise measurement of the reactor neutrino’s oscillation spectrum, an atmospheric neutrino oscillation measurement in JUNO offers independent sens itivity for NMO, which can potentially increase JUNO’s total sensitivity in a jo int analysis. In this contribution, we present a novel multi-purpose reconstruct ion method for atmospheric neutrinos in JUNO at few-GeV based on a machine learn ing technique. This method extracts features related to event topology from PMT waveforms and uses them as inputs to machine learning models. A preliminary stud y based on the JUNO simulation shows good performances for event directionality reconstruction and neutrino flavor identification.”
Key words
Shandong University/Cyborgs/Emerging T echnologies/Machine Learning/Neutrinos/Physics
NETL
NSTL