New developments in vertex reconstruction for CMS

Presently, two kinds of least-squares (LS) vertex fits are implemented in the ORCA reconstruction program (http://cmsdoc.cern.ch /orca) of the CMS experiment (http://cmsinfo.cern.ch): a full Kalman filter, and an iterative fit working with the impact points of the tracks with respect to an expansion...

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Bibliographic Details
Published in:Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment
Main Authors: Frühwirth, R, Prokofiev, K, Speer, T, Vanlaer, P, Waltenberger, W
Language:English
Published: 2003
Subjects:
Detectors and Experimental Techniques
Orca
Online Access:https://doi.org/10.1016/S0168-9002(03)00548-5
http://cds.cern.ch/record/624962
Description
Summary:Presently, two kinds of least-squares (LS) vertex fits are implemented in the ORCA reconstruction program (http://cmsdoc.cern.ch /orca) of the CMS experiment (http://cmsinfo.cern.ch): a full Kalman filter, and an iterative fit working with the impact points of the tracks with respect to an expansion point. In this contribution we concentrate on nonlinear, robust estimators which are insensitive to outlying observations. The aim is to improve the recognition of outliers, to lower the bias in the final fit, and to achieve a better separation between primary vertices and secondary vertices. Robust vertex estimates should also be good starting points for more complex algorithms, such as a multivertex fit.

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