Aidar Ilyasov (National Research Centre "Kurchatov Institute") "Event reconstruction in liquid noble gas particle detectors using machine learning methods"
This problem is particularly relevant for low-background detectors. The classical techniques used to reduce the number of background processes in the detector's target cannot always eliminate background events related to the design features of the experimental setup.
Machine learning is a modern method for both generating new synthetic data and analyzing existing physical data. In this work, it is used for the accurate reconstruction of events and for improving the accuracy of the low-background detector. Through the application of the machine learning method, it was possible to both expand the analyzed volume of the detector and establish new event selection criteria that eliminate the influence of the detector's design features on the data analysis.
The results of the study will enable the search for dark matter interactions with the target nucleus at lower scattering cross-sections.
Link to watch the video on the JINR resource:
https://disk.jinr.ru/index.php/s/bjWTaoaoL3yFwPC
