June 11, 2023
Journal Article
Development and Performance Evaluation of a Novel y-y Coincidence Analysis Software
Abstract
A novel ?-? coincidence identification software has been developed at Pacific Northwest National Laboratory, USA. The software requires time-stamped list (TLIST) data from time-synchronized detectors. The software uses binary search to readily identify coincidence pairs of interest and has been implemented using Python programming language. This work presents software’s development, performance, and validation using both synthetic and experimental data. Performance of various strategies/libraries employed in the software and their merits is also highlighted.Published: June 11, 2023