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AKPIK: Arbeitskreis Physik, moderne Informationstechnologie und Künstliche Intelligenz
AKPIK 1: AKPIK I
AKPIK 1.4: Vortrag
Mittwoch, 1. April 2020, 17:15–17:30, H-HS XII
Belle II pixeldetector cluster analyses using neural network algorithms — Stephanie Kaes1, Irina Heinz1, Soeren Lange1, and •Katharina Dort1,2 for the Belle II collaboration — 1II Physics Institute, Justus Liebig University Giessen, Germany — 2CERN, Geneva, Switzerland
The Belle II DEPFET pixeldetector is operating since 2019, presently with 4M pixels and trigger rates up to 5 kHz. The pixeldetector has the unique ability to detect exotic highly ionizing particles such as antideuterons or stable tetraquarks which due to their high energy loss do not reach the outer sub-detectors, and thus generate no reconstructable track. In order to identify these highly ionizing particles multivariate analyses of pixeldetector clusters is performed. The multidimensional input space consists of variables such as single-pixel signals, cluster observables, or Zernicke moments. We present results for cluster classification using three different neural network algorithms: multilayer perceptrons, Kohonen-type networks (often denoted as self-organizing maps) and Hopfield-type networks (often denoted as associate memories). Data preprocessing by Principal Components analysis and possible implementation on an FPGA for online reconstruction are discussed as well.