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T: Fachverband Teilchenphysik

T 42: Experimentelle Methoden I

T 42.9: Vortrag

Dienstag, 26. März 2019, 18:05–18:20, ST 1

First Level Neural Network z-Trigger Optimization and Implementation in the Drift Chamber of the Belle II Experiment — •Sara McCarney, Christian Kiesling, Felix Meggendorfer, and Sebastian Skambraks — Max Planck Institute for Physics, Munich, Germany

For the Belle II experiment at the SuperKEKB asymmetric electron-positron collider (KEK, Japan), a z-trigger for Belle II is required to suppress the dominating background of tracks from outside of the collision point. The concept of a first level track trigger, realized by neural networks, is presented. The Multi Layer Perceptron (MLP) Neural Network, using drift times and a traditional Hough-based 2D track finder as input, reconstructs the origin of the tracks along the beam's z-axis. Training and testing on simulated tracks achieve resolutions below 2 cm in the high Pt region, and below 5 cm in the low Pt region, sufficient for efficient background rejection. The importance of various training parameters and drift time inputs on the optimal spatial resolution of the z-trigger is discussed. Background distributions from first data taking with Belle II are analyzed to optimize suitable z-cuts for an efficient background suppression.