Track finding at Belle II

• DOI: 10.1016/j.cpc.2020.107610
• Publication Date: 2020-10-02T01:05:04Z
• Authors: Valerio Bertacchi; Tadeas Bilka; Nils Braun; Giulia Casarosa; Luigi Corona; Sam Cunliffe; Filippo Dattola; Gaetano De Marino; Michael De Nuccio; Giacomo De Pietro; Thanh Van Dong; Giulio Dujany; Patrick Ecker; Michael Eliachevitch; Tristan Fillinger; Oliver Frost; Rudolf Frühwirth; Uwe Gebauer; Sasha Glazov; Nicolas Gosling; Aiqiang Guo; Thomas Hauth; Martin Heck; Mateusz Kaleta; Jakub Kandra; Claus Kleinwort; Thomas Kuhr; Simon Kurz; Peter Kvasnicka; Jakob Lettenbichler; Thomas Lueck; Alberto Martini; Felix Metzner; Dmitrii Neverov; Carsten Niebuhr; Eugenio Paoloni; Sourav Patra; Leo Piilonen; Cyrille Praz; Markus Tobias Prim; Christian Pulverm...; Sebastian Racs; Navid Rad; Petar Rados; Martin Ritter; Giuliana Rizzo; Armine Rostomyan; Bianca Scavino; Tobias Schlüter; Benjamin Schwenker; Stefano Spataro; Björn Spruck; Henrikas Svidras; Francesco Tenchini; Yuma Uematsu; James Webb; Christian Wessel; Laura Zani
• Keywords: data analysis method; Physics - Instrumentation and Detectors; FOS: Physical sciences; BELLE; 530; programming; 01 natural sciences; High Energy Physics - Experiment; Tracking algorithms; Tracking detectors; 03 medical and health sciences; High Energy Physics - Experiment (hep-ex); 0302 clinical medicine; 0103 physical sciences; Belle II; Tracking algorithms; Tracking detectors; [PHYS.HEXP]Physics [physics]/High Energy Physics - Experiment [hep-ex]; Belle II; [PHYS.PHYS.PHYS-INS-DET]Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det]; info:eu-repo/classification/ddc/530; track data analysis; Physics; ddc:530; Instrumentation and Detectors (physics.ins-det); charged particle; performance

This paper describes the track-finding algorithm that is used for event reconstruction in the Belle II experiment operating at the SuperKEKB B-factory in Tsukuba, Japan. The algorithm is designed to balance the requirements of a high efficiency to find charged particles with a good track parameter resolution, a low rate of spurious tracks, and a reasonable demand on CPU resources. The software is implemented in a flexible, modular manner and employs a diverse selection of global and local track-finding algorithms to achieve an optimal performance.