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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.
One of the most computationally challenging problems expected for the High-Luminosity Large Hadron Collider (HL-LHC) is determining the trajectory of charged particles during event reconstruction. Algorithms used at the LHC today rely on Kalman filte
We describe the Hybrid seeding, a standalone pattern recognition algorithm aiming at finding charged particle trajectories for the LHCb upgrade. A significant improvement to the charged particle reconstruction efficiency is accomplished by exploiting
In the context of track fitting problems by a Kalman filter, the appropriate functional forms of the elements of the random process noise matrix are derived for tracking through thick layers of dense materials and magnetic field. This work complement
This article describes a new charged-particle track fitting algorithm designed for use in high-speed electronics applications such as hardware-based triggers in high-energy physics experiments. Following a novel technique designed for fast electronic
A Kalman filter package has been developed for reconstructing muon ($mu^pm$) tracks (coming from the neutrino interactions) in ICAL detector. Here, we describe the algorithm of muon track fitting, with emphasis on the error propagation of the element