Karlsruhe 2024 – scientific programme

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T: Fachverband Teilchenphysik

T 33: Neutrino physics 4

T 33.4: Talk

Tuesday, March 5, 2024, 16:45–17:00, Geb. 30.21: Gerthsen-HS

Machine Learning for background discrimination in LEGEND200 — •Sean Sullivan — MPIK, Heidelberg, Germany

The development of Neural Networks has generated an array of powerful analysis techniques for modern scientific experiments. Particularly in areas of classification and background reduction. This talk will discuss the application of such techniques to the LEGEND200 experiment for neutrinoless double beta decay: an as yet unobserved process beyond the standard model for which background reduction is a keystone. LEGEND200 employs High Purity Germanium detectors enriched in Germanium-76 operated in a liquid argon cryostat. Important backgrounds that must be excluded include multi-site events and surface alphas. Established methods for dealing with these backgrounds can be compared with Machine Learning techniques.

Keywords: Neutrinoless Double Beta Decay; Machine Learning