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Anti-electron Neutrino Event Selection from Backgrounds Based on Machine Learning
- Publication Year :
- 2019
-
Abstract
- For reactor neutrino experiments including the next--generation experiments will be adopting the liquid scintillator technique, criteria and time to select neutrino--induced inverse beta decay events from the background events need to be established. For higher performance efficiency, we investigated the results of applying a machine learning technique embedded in a standard ROOT package to select IBD signals. To obtain a higher statistics, the signals and background events in a gadolinium-loaded liquid scintillation detector were reproduced by Monte Carlo simulation. We report the efficiencies of neutrino--induced $n-H$ and $n-Gd$ events selection using the machine learning technique.<br />Comment: 9 pages, 9 figures
- Subjects :
- High Energy Physics - Experiment
Physics - Instrumentation and Detectors
Subjects
Details
- Database :
- arXiv
- Publication Type :
- Report
- Accession number :
- edsarx.1907.05635
- Document Type :
- Working Paper