Testing Automatic Cut Finding Tool Performance for HADES Event Selection Optimization

As part of the international collaboration at the FAIR - GSI accelerator facility in Germany, a testing process has been conducted on the performance of an automatic cut finding tool for optimizing event selection as compared to the manual cutting process. Manually making cuts is a standard practice in hadron physics analysis but is known to take a considerable amount of time, and the analysis process is significantly streamlined by the introduction of an automatic tool. The cut finder accepts ROOT files containing data taken for measured collision variables, and chooses the most optimal subgroup of these variables on which to make cuts that lead to the best signal extraction and background suppression. For the first time, the tool was tested with experimental data from the HADES (High Acceptance Di-Electron Spectrometer) experiment, specifically events containing long-lived hyperons. This was done by first running the tool with simulated toy Monte Carlo signal and background data, followed by experimental data taken from beamtime in February of 2022. It was found that in both simulations and the lab setting, the automatic cut finder consistently chose the particle momentum components, decay vertices, and the polar angle to be the most optimal for cutting on in cases containing long-lived hyperon events. In this poster session I will be presenting the results of my work at GSI and my ideas for future applications.