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
Main Authors: Frühwirth, Rudolf, Prokofiev, K., Speer, Thomas, Vanlaer, Pascal, Waltenberger, Wolfgang
Format: Article in Journal/Newspaper
Language:English
Published: 2003
Subjects:
Physique des particules élémentaires
Kalman filter
Robust estimators
Vertex reconstruction
Orca
Online Access:http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/170959
https://dipot.ulb.ac.be/dspace/bitstream/2013/170959/1/Elsevier_154589.pdf
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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. © 2003 Elsevier Science B.V. All rights reserved. SCOPUS: cp.j info:eu-repo/semantics/published

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