A neural network z-vertex trigger for Belle II

S. Neuhaus, S. Skambraks, F. Abudinen, Y. Chen, M. Feindt, R. Frühwirth, M. Heck, C. Kiesling, A. Knoll, S. Paul, J. Schieck

Research output: Contribution to journalConference articlepeer-review

13 Scopus citations

Abstract

We present the concept of a track trigger for the Belle II experiment, based on a neural network approach, that is able to reconstruct the z (longitudinal) position of the event vertex within the latency of the first level trigger. The trigger will thus be able to suppress a large fraction of the dominating background from events outside of the interaction region. The trigger uses the drift time information of the hits from the Central Drift Chamber (CDC) of Belle II within narrow cones in polar and azimuthal angle as well as in transverse momentum (sectors), and estimates the z-vertex without explicit track reconstruction. The preprocessing for the track trigger is based on the track information provided by the standard CDC trigger. It takes input from the 2D (r - φ) track finder, adds information from the stereo wires of the CDC, and finds the appropriate sectors in the CDC for each track in a given event. Within each sector, the z-vertex of the associated track is estimated by a specialized neural network, with a continuous output corresponding to the scaled z-vertex. The input values for the neural network are calculated from the wire hits of the CDC.

Original languageEnglish
Article number012052
JournalJournal of Physics: Conference Series
Volume608
Issue number1
DOIs
StatePublished - 22 May 2015
Event16th International Workshop on Advanced Computing and Analysis Techniques in Physics Research: Bridging Disciplines, ACAT 2014 - Prague, Czech Republic
Duration: 1 Sep 20145 Sep 2014

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