Reconstruction of Electron Tracks With the Gaussian-Sum Filter

Due to the highly non-Gaussian shape of the bremsstrahlung energy loss distribution the standard Kalman filter is not the optimal algorithm for the reconstruction of electron tracks, since it implicitely assumes that all noise probability density functions involved are Gaussian. A Gaussian-sum filter (GSF) algorithm for electron track reconstruction in the CMS Tracker at LHC has therefore been developed. The basic idea is to model the bremsstrahlung distribution by a Gaussian mixture rather than a single Gaussian. It is shown that the GSF is able to improve the momentum resolution of electrons compared to the standard Kalman filter. The impact of the number of components in the mixture on the quality and the precision of the estimates is studied.