Abstract

The track trigger is one of the main components of the Belle II first level trigger, taking input from the Central Drift Chamber (CDC). It consists of several stages, first combining hits to track segments, followed by a 2D track finding in the transverse plane and finally a 3D track reconstruction. The results of the track trigger are the track multiplicity, the momentum vector of each track and the longitudinal displacement of the origin or production vertex of each track (“z-vertex”). The latter allows to reject background tracks from outside of the interaction region and thus to suppress a large fraction of the machine background. This contribution focuses on the track finding stage using Hough transforms and on the z-vertex reconstruction with neural networks. We describe the algorithms and show performance studies on simulated events.

Highlights

  • Belle II [1] is an upgrade of the Belle experiment, which is currently being constructed at KEK in Tsukuba, Japan

  • About 3 to 9 tracks are typically visible in the track trigger, while the background track multiplicity is relatively low, producing rarely more than two visible tracks

  • For events with two tracks, different z-vertex constraints are compared: either both tracks are required to come from the interaction point (IP) or at least one of them, where an IP track is characterized by an estimated z-vertex within ±10 cm

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Summary

Introduction

Belle II [1] is an upgrade of the Belle experiment, which is currently being constructed at KEK in Tsukuba, Japan. Examples include B decays to invisible final states and τ pair events The latter will be produced at SuperKEKB with a cross section of the same order of magnitude as the Υ(4S) cross section, so τ physics are an important aspect of the Belle II physics program. Interactions (Touschek scattering [3]) and collisions with residual gas in the beampipe This background can be suppressed by reconstructing the z-vertex of each track and rejecting tracks that do not originate at the interaction point, that is it requires a 3D track reconstruction. A Bhabha veto will be based on tracks that are matched with clusters in the electromagnetic calorimeter This matching algorithm requires a 3D track reconstruction to obtain the polar angle and the total momentum of the track

The track trigger
Track segment finder
Track vertex reconstruction
Performance
Background rejection
Track trigger efficiency
Findings
Conclusion
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