A data analysis suite for neutron time correlation measurements

The analysis of time-correlated events in passive neutron counting allows, under certain circumstances, the mass determination of samples containing radionuclides emitting neutrons by spontaneous fission. List mode data can be generated during passive neutron counting measurements or simulations. These data require further processing to produce the observables of interest for time-correlation analysis such as the multiplicity distributions in a given time window or the so-called Rossi-Alpha distribution. For this purpose, a C/C++ code was written at SCK CEN as well as a suite of Python scripts to cover additional steps in the data analysis of neutron multiplicity measurements. In this paper, we describe the main features of the list mode data processing code, report about its performance and benchmark with other codes that were used in the ESARDA Multiplicity Benchmark Exercise. In addition, the overall data analysis framework for the determination of the mass of the assayed sample is also explained. Such framework uses the either generalized point model equations or a calibration approach and its implementation by means of Python scripts is explained. The application of the whole data analysis suite is presented by using data from measurements with certified reference material.