Development and performance evaluation of a novel γ-γ coincidence analysis software

Processing of large amounts of data from a gamma-gamma coincidence system is a practical challenge in trace-level radionuclide measurements. Given the benefits and growing number of multidimensional gamma spectrometers worldwide, this is a major restriction in wide-spread applicability of coincidence techniques. This study demonstrates a novel gamma-gamma coincidence analysis software developed at Pacific Northwest National Laboratory, USA. The software utilizes advanced search techniques and Python libraries to readily identify coincidence signatures in the large data. Using both synthetic and experimental data, the study uncovers various strategies/libraries employed during software's development. This work aims to provide a reference document in handling large data routinely encountered in trace-level measurements.

Automated summary

Processing large amounts of data is a challenge in trace-level radionuclide measurements, limiting the widespread use of coincidence techniques with multidimensional gamma spectrometers. This study presents a new gamma-gamma coincidence analysis software developed at Pacific Northwest National Laboratory, USA. The software utilizes advanced search techniques and Python libraries to quickly identify coincidence signatures in large data, providing a reference document for handling large data encountered in trace-level measurements.