Pseudo-Data Generation for Applications to the In-Beam Neutron Lifetime Measurement

The free neutron lifetime is a crucial input parameter in big bang nucleosynthesis calculations and in our understanding of the weak force, yet discrepancies in its measurement have persisted for over a decade. The two classes of experiments, the ``bottle'' and ``beam'' methods, have disagreed by over 4$\sigma $. To better understand this discrepancy, the newest generation neutron lifetime measurements are pushing for higher precision. In order to help achieve this goal, a pseudo-data set was generated for the beam lifetime experiment to benchmark current data analysis techniques as well as test new machine learning algorithms. The materials to be presented in this talk include pseudo-data generation methods, types of events created, and comparison to real data.