Functional Analysis of Neutron-Gamma Pulses and Synthetic Pulse Generation for Liquid Scintillator

Abstract

An innovative method is proposed to generate a realistic functional neutron and gamma pulses model for a liquid scintillator-based detector. This approach analyzed neutron and gamma pulse shapes, electronic noise, and fit the model parameters that include the intrinsic properties of the scintillator and standard deviation of the transit time of the photomultiplier tube (PMT). The synthetic data are generated using Monte-Carlo (MC)-based statistical methods from the modeled functions, energy distributions of neutrons, gammas, and electronic noise. This work emulates realistic pulses that can be used to calibrate and test scintillation detectors used in nuclear physics experiments. This synthetic data library provides realistic labeled neutron and gamma pulses for liquid scintillators and PMTs, which may be used for improving radiation detection through supervised machine learning. This study provides a comprehensive framework for neutron-gamma discrimination, synthetic data generation, and data validation.