Least squares approach to the alignment of the generic high precision tracking system

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A least squares method to solve a generic alignment problem of a high granularity tracking system is presented. The algorithm is based on an analytical linear expansion and allows for multiple nested fits, e.g. imposing a common vertex for groups of particle tracks is of particular interest. We pres...

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Detalles Bibliográficos
Autores principales: Bruckman de Renstrom, Pawel, Haywood, S
Lenguaje:eng
Publicado: 2006
Materias:
Detectors and Experimental Techniques
Acceso en línea:https://dx.doi.org/10.1142/9781860948985_0015
http://cds.cern.ch/record/2743147
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author Bruckman de Renstrom, Pawel
Haywood, S
author_facet Bruckman de Renstrom, Pawel
Haywood, S
author_sort Bruckman de Renstrom, Pawel
collection CERN
description A least squares method to solve a generic alignment problem of a high granularity tracking system is presented. The algorithm is based on an analytical linear expansion and allows for multiple nested fits, e.g. imposing a common vertex for groups of particle tracks is of particular interest. We present a consistent and complete recipe to impose constraints on either implicit or explicit parameters. The method has been applied to the full simulation of a subset of the ATLAS silicon tracking system. The ultimate goal is to determine ≈35,000 degrees of freedom (DoF's). We present a limited scale exercise exploring various aspects of the solution.
id oai-inspirehep.net-706573
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2006
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spelling oai-inspirehep.net-7065732020-11-04T20:05:17Zdoi:10.1142/9781860948985_0015http://cds.cern.ch/record/2743147engBruckman de Renstrom, PawelHaywood, SLeast squares approach to the alignment of the generic high precision tracking systemDetectors and Experimental TechniquesA least squares method to solve a generic alignment problem of a high granularity tracking system is presented. The algorithm is based on an analytical linear expansion and allows for multiple nested fits, e.g. imposing a common vertex for groups of particle tracks is of particular interest. We present a consistent and complete recipe to impose constraints on either implicit or explicit parameters. The method has been applied to the full simulation of a subset of the ATLAS silicon tracking system. The ultimate goal is to determine ≈35,000 degrees of freedom (DoF's). We present a limited scale exercise exploring various aspects of the solution.oai:inspirehep.net:7065732006
spellingShingle Detectors and Experimental Techniques
Bruckman de Renstrom, Pawel
Haywood, S
Least squares approach to the alignment of the generic high precision tracking system
title Least squares approach to the alignment of the generic high precision tracking system
title_full Least squares approach to the alignment of the generic high precision tracking system
title_fullStr Least squares approach to the alignment of the generic high precision tracking system
title_full_unstemmed Least squares approach to the alignment of the generic high precision tracking system
title_short Least squares approach to the alignment of the generic high precision tracking system
title_sort least squares approach to the alignment of the generic high precision tracking system
topic Detectors and Experimental Techniques
url https://dx.doi.org/10.1142/9781860948985_0015
http://cds.cern.ch/record/2743147
work_keys_str_mv AT bruckmanderenstrompawel leastsquaresapproachtothealignmentofthegenerichighprecisiontrackingsystem
AT haywoods leastsquaresapproachtothealignmentofthegenerichighprecisiontrackingsystem

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