Reconstruction of electrons with the Gaussian-sum filter in the CMS tracker at the LHC

By W. Adam, R. Fruhwirth, A. Strandlie, T. Todorov. 2003

231 citations recorded by the source corpus.

The bremsstrahlung energy loss distribution of electrons propagating in matter is highly non Gaussian. Because the Kalman filter relies solely on Gaussian probability density functions, it might not be an optimal reconstruction algorithm for electron tracks. A Gaussian-sum filter (GSF) algorithm for electron track reconstruction in the CMS tracker has therefore been developed. The basic idea is to model the bremsstrahlung energy loss 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 momentum resolution and the quality of the estimated error are studied with various types of mixture models of the energy loss distribution.

Subfields: Nuclear and High Energy Physics

View Paper: https://www.semanticscholar.org/paper/9560428ebe7a7857525346820075dc79f0753de0

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In Nuclear and High Energy Physics

Citations in the corpus

Performance of the CMS missing transverse momentum reconstruction in pp data at √s = 8 TeV (2014, methodology): “Electrons are identified as primary charged-particle tracks reconstructed by a Gaussian-sum filter (GSF) algorithm [7] and matched to ECAL energy clusters; the matching allows for associated bremsstrahlung photons.”
Particle-flow reconstruction and global event description with the CMS detector (2017, methodology): “The GSF fitting is more adapted to electrons than the KF used in the iterative tracking, as it allows for sudden and substantial energy losses along the trajectory.”
Performance of electron reconstruction and selection with the CMS detector in proton-proton collisions at √s=8 TeV (2015, methodology): “The electron candidates are constructed from the association of a GSF track and a cluster in the ECAL.”
Measurement of the Inclusive W and Z Production Cross Sections in pp Collisions at sqrt(s) = 7 TeV (2011, methodology): “Electron tracks are reconstructed using an algorithm [35] (Gaussian-sum filter, or GSF tracking) that accounts for possible energy loss due to bremsstrahlung in the tracker layers.”
RAVE—A Detector-Independent Toolkit to Reconstruct Vertices (2011, methodology): “The Gaussian-sum track fitter [45] is a track fitting method that accounts for such effects.”
Description and performance of track and primary-vertex reconstruction with the CMS tracker: JINST 9 (2014) 10, P10009 (2014, methodology): “To obtain the best parameter estimates, the final track fit is performed using a modified version of the Kalman filter, called the Gaussian Sum Filter (GSF) [37].”
Performance of photon reconstruction and identification with the CMS detector in proton-proton collisions at √s = 8 TeV (2015, methodology): “All tracks associated to the main electron reconstruction [18], as well as the subsample of the standard tracks which can be associated to energy deposits in the ECAL, are possible electron candidates and are refitted with the Gaussian sum filter method [38].”
Performance of electron reconstruction and selection with the CMS detector in proton-proton collisions at √s = 8 TeV (2015, methodology): “The electron candidates are constructed from the association of a GSF track and a cluster in the ECAL.”
Measurement of the inclusive W and Z production cross sections in pp collisions at $ \sqrt {s} = 7 $ TeV with the CMS experiment (2011, methodology): “Electron tracks are reconstructed using an algorithm [35] (Gaussian-sum filter, or GSF tracking) that accounts for possible energy loss due to bremsstrahlung in the tracker layers.”