Aachen 2019 – scientific programme

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T: Fachverband Teilchenphysik

T 42: Experimentelle Methoden I

T 42.7: Talk

Tuesday, March 26, 2019, 17:35–17:50, ST 1

3D Track Finding in the Preprocessing of the Belle II L1 Neural Network z-Vertex Trigger — •Sebastian Skambraks, Christian Kiesling, Sara McCarney, and Felix Meggendorfer for the Belle 2 collaboration — MPI for Physics

Neural networks are going to be used in the pipelined first level trigger of the upgraded flavor physics experiment Belle II at the high luminosity B factory SuperKEKB in Tsukuba, Japan. An instantaneous luminosity of L = 8 × 10³⁵cm⁻²s⁻¹ is anticipated, 40 times larger than the world record reached with the predecessor KEKB. Background tracks, with vertices displaced along the beamline (z-axis), are expected to be severely increased due to the high luminosity. Using the hit and drift time information from the central drift chamber, the online neural network trigger estimates the 3D track parameters of single tracks found by the track finder. This robust estimation of the z-vertices significantly improves the suppression of displaced background tracks. A machine learning based extension of the conventional 2D Hough track finder to 3D is discussed, which allows to use the stereo sense wire information in the track finding and thus to improve the track finding efficiency. The estimated polar track angle can be used for a further specialization of the following neural networks to phase space sectors.