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Implementation of GENFIT2 as an experiment independent track-fitting framework

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arxiv 1902.04405 v2 pith:YYMTLP54 submitted 2019-02-12 physics.data-an physics.ins-det

Tadeas Bilka , Nils Braun , Thomas Hauth , Thomas Kuhr , Lia Lavezzi , Felix Metzner , Stephan Paul , Elisabetta Prencipe
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Markus Prim Johannes Rauch James Ritman Tobias Schlueter Stefano Spataro
This is my paper · ORCID
classification physics.data-anphysics.ins-det
keywords genfit2experimentgeneralgenfitimplementationparametersprovidestrack
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The GENFIT toolkit, initially developed at the Technische Universitaet Muenchen, has been extended and modified to be more general and user-friendly. The new GENFIT, called GENFIT2, provides track representation, track-fitting algorithms and graphic visualization of tracks and detectors, and it can be used for any experiment that determines parameters of charged particle trajectories from spacial coordinate measurements. Based on general Kalman filter routines, it can perform extrapolations of track parameters and covariance matrices. It also provides interfaces to Millepede II for alignment purposes, and RAVE for the vertex finder. Results of an implementation of GENFIT2 in basf2 and PandaRoot software frameworks are presented here.

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Forward citations

Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. End-to-End Multi-Track Reconstruction using Graph Neural Networks at Belle II

    physics.ins-det 2024-11 conditional novelty 7.0 of 10

    A GNN-based end-to-end track finder for the Belle II drift chamber reconstructs displaced tracks at 85.4% efficiency with a 2.5% fake rate, outperforming the baseline algorithm at 52.2%.

  2. Mitigating Detector Ageing Effects with Graph-Based Multi-Modal Track Reconstruction at Belle II

    hep-ex 2026-07 conditional novelty 5.0 of 10

    Retraining a graph-neural-network track finder on degraded Belle II CDC conditions recovers track efficiency and purity better than the staged baseline reconstruction.

  3. GPU Tracking in the COMET Phase-I Cylindrical Drift Chamber

    physics.ins-det 2019-08 conditional novelty 5.0 of 10

    A parallel, GPU-based seed-scanning track finder with Hough-transform initialization finds multiple-turn electron tracks in COMET Phase-I Monte Carlo events at 33x CPU speedup and about 300 keV momentum resolution.

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