Speaker
Johannes Rauch
(T)
Description
Genfit is an experiment-independent track-fitting toolkit, which combines fitting algorithms,
track representations, and measurement geometries into a modular framework. We report
on a significantly improved version of Genfit, based on experience gained in the Belle II,
PANDA, and FOPI experiments. Improvements concern the implementation of additional
track-fitting algorithms, enhanced implementations of Kalman fitters, enhanced visualization
capabilities, and additional implementations of measurement types suited for various kinds
of tracking detectors. The data model has been revised, allowing for efficient track merging,
smoothing, residual calculation and alignment.
Summary
Genfit is an experiment-independent track-fitting toolkit, which combines fitting algorithms,
track representations, and measurement geometries into a modular framework. We report
on a significantly improved version of Genfit, based on experience gained in the Belle II,
PANDA, and FOPI experiments. Improvements concern the implementation of additional
track-fitting algorithms, enhanced implementations of Kalman fitters, enhanced visualization
capabilities, and additional implementations of measurement types suited for various kinds
of tracking detectors. The data model has been revised, allowing for efficient track merging,
smoothing, residual calculation and alignment.
Primary authors
Johannes Rauch
(T)
Tobias Schlueter
(Theoretische Physik-Fakultaet fuer Physik-Ludwig-Maximilians-Uni)
