Abstract
We present an alternative implementation of the Kalman filter employed for track fitting within the LHCb experiment. It uses simple parametrizations for the extrapolation of particle trajectories in the field of the LHCb dipole magnet and for the effects of multiple scattering in the detector material. A speedup of more than a factor of four is achieved while maintaining the quality of the estimated track quantities. This Kalman filter implementation could be used in the purely software-based trigger of the LHCb upgrade.
Highlights
The LHCb experiment is a dedicated heavy flavour physics experiment at the LHC focusing on the study of hadrons containing b and c quarks [1]
We presented an alternative implementation of a Kalman filter for the LHCb experiment
Based on simple parametrizations of material effects and the extrapolation through the magnetic field of the detector, this algorithm achieves a significant speedup with respect to the current implementation, while retaining comparable quality of the track parameters
Summary
The LHCb experiment is a dedicated heavy flavour physics experiment at the LHC focusing on the study of hadrons containing b and c quarks [1]. During Runs 1 and 2 of the LHC, this trigger system consisted of a hardware stage, reducing the rate from 40 MHz to 1 MHz, followed by a two-stage software trigger In the latter, the full tracking system was read out and a partial (first stage) and full (second stage) event reconstruction were performed [2]. The Kalman filter which was used during Run 1 and 2 in LHCb, in the following called default Kalman, is significantly too slow It relies on lookup tables for the magnetic field and the material distribution of the detector [11], so-called maps. Accessing the values in the lookup table and solving the differential equations are time consuming and prohibit the usage of the current Kalman filter in the first stage of the upgraded trigger system. It obtains precise values of track parameters and track quality variables, while relying on neither computationally costly extrapolation methods nor material or magnetic field maps
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