Neutron–gamma discrimination based on quantum clustering technique

In this study, the digital neutron–gamma discrimination (DNGD) has been undertaken based on the pulse-shape discrimination on the anode pulse of a 2" by 2" right cylinder BC501A liquid scintillator with a fast data acquisition card (14-bit resolution, 500 MS/s). Seven different features of the anode pulse have been extracted and the discrimination based on quantum clustering (DBQC) has been studied. The influence of three different parameters (i.e., $\eta$, $\sigma$ and K) on the discrimination figure-of-merit (FoM) has been investigated. In addition, the FoM dependencies on different choices of DBQC features have been determined. A 100 mCi ²⁴¹Am-Be neutron source has been used for the DNGD and the calibration has been made with a 1.1 $\mu$Ci ²²Na gamma-ray source. The results show that the FoM value is around 1 at 100 keVee bias energy, whilst this value can be improved up to 50% by choosing and setting appropriate features.