Forward Tracking in the ILD Detector

The reconstruction software for ILD is currently subject to a major revision, aiming at improving its accuracy, speed, efficiency and maintainability in time for the upcoming DBD Report. This requires replacing old code by novel methods for track search and fit, together with modern standards for in...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:arXiv.org 2012-02
Hauptverfasser: Glattauer, Robin, Frühwirth, Rudolf, Lettenbichler, Jakob, Mitaroff, Winfried
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page
container_issue
container_start_page
container_title arXiv.org
container_volume
creator Glattauer, Robin
Frühwirth, Rudolf
Lettenbichler, Jakob
Mitaroff, Winfried
description The reconstruction software for ILD is currently subject to a major revision, aiming at improving its accuracy, speed, efficiency and maintainability in time for the upcoming DBD Report. This requires replacing old code by novel methods for track search and fit, together with modern standards for interfaces and tools. Track reconstruction in the "forward region", defined by the silicon Forward Tracking Detector (FTD), relies heavily on a powerful stand-alone track search. The new software makes use of a Cellular Automaton, a Kalman filter, and a Hopfield Neural Network. We give an overview of the project, its methods and merits.
format Article
fullrecord <record><control><sourceid>proquest</sourceid><recordid>TN_cdi_proquest_journals_2085862467</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2085862467</sourcerecordid><originalsourceid>FETCH-proquest_journals_20858624673</originalsourceid><addsrcrecordid>eNpjYuA0MjY21LUwMTLiYOAtLs4yMDAwMjM3MjU15mRQccsvKk8sSlEIKUpMzs7MS1fIzFMoyUhV8PRxUXBJLUlNLskv4mFgTUvMKU7lhdLcDMpuriHOHroFRfmFpanFJfFZ-aVFeUCpeCMDC1MLMyMTM3Nj4lQBAHhbLdw</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2085862467</pqid></control><display><type>article</type><title>Forward Tracking in the ILD Detector</title><source>Freely Accessible Journals</source><creator>Glattauer, Robin ; Frühwirth, Rudolf ; Lettenbichler, Jakob ; Mitaroff, Winfried</creator><creatorcontrib>Glattauer, Robin ; Frühwirth, Rudolf ; Lettenbichler, Jakob ; Mitaroff, Winfried</creatorcontrib><description>The reconstruction software for ILD is currently subject to a major revision, aiming at improving its accuracy, speed, efficiency and maintainability in time for the upcoming DBD Report. This requires replacing old code by novel methods for track search and fit, together with modern standards for interfaces and tools. Track reconstruction in the "forward region", defined by the silicon Forward Tracking Detector (FTD), relies heavily on a powerful stand-alone track search. The new software makes use of a Cellular Automaton, a Kalman filter, and a Hopfield Neural Network. We give an overview of the project, its methods and merits.</description><identifier>EISSN: 2331-8422</identifier><language>eng</language><publisher>Ithaca: Cornell University Library, arXiv.org</publisher><subject>Cellular automata ; Kalman filters ; Maintainability ; Neural networks ; Reconstruction ; Software ; Tracking</subject><ispartof>arXiv.org, 2012-02</ispartof><rights>2012. This work is published under http://arxiv.org/licenses/nonexclusive-distrib/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>781,785</link.rule.ids></links><search><creatorcontrib>Glattauer, Robin</creatorcontrib><creatorcontrib>Frühwirth, Rudolf</creatorcontrib><creatorcontrib>Lettenbichler, Jakob</creatorcontrib><creatorcontrib>Mitaroff, Winfried</creatorcontrib><title>Forward Tracking in the ILD Detector</title><title>arXiv.org</title><description>The reconstruction software for ILD is currently subject to a major revision, aiming at improving its accuracy, speed, efficiency and maintainability in time for the upcoming DBD Report. This requires replacing old code by novel methods for track search and fit, together with modern standards for interfaces and tools. Track reconstruction in the "forward region", defined by the silicon Forward Tracking Detector (FTD), relies heavily on a powerful stand-alone track search. The new software makes use of a Cellular Automaton, a Kalman filter, and a Hopfield Neural Network. We give an overview of the project, its methods and merits.</description><subject>Cellular automata</subject><subject>Kalman filters</subject><subject>Maintainability</subject><subject>Neural networks</subject><subject>Reconstruction</subject><subject>Software</subject><subject>Tracking</subject><issn>2331-8422</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2012</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNpjYuA0MjY21LUwMTLiYOAtLs4yMDAwMjM3MjU15mRQccsvKk8sSlEIKUpMzs7MS1fIzFMoyUhV8PRxUXBJLUlNLskv4mFgTUvMKU7lhdLcDMpuriHOHroFRfmFpanFJfFZ-aVFeUCpeCMDC1MLMyMTM3Nj4lQBAHhbLdw</recordid><startdate>20120213</startdate><enddate>20120213</enddate><creator>Glattauer, Robin</creator><creator>Frühwirth, Rudolf</creator><creator>Lettenbichler, Jakob</creator><creator>Mitaroff, Winfried</creator><general>Cornell University Library, arXiv.org</general><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>L6V</scope><scope>M7S</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope></search><sort><creationdate>20120213</creationdate><title>Forward Tracking in the ILD Detector</title><author>Glattauer, Robin ; Frühwirth, Rudolf ; Lettenbichler, Jakob ; Mitaroff, Winfried</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-proquest_journals_20858624673</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Cellular automata</topic><topic>Kalman filters</topic><topic>Maintainability</topic><topic>Neural networks</topic><topic>Reconstruction</topic><topic>Software</topic><topic>Tracking</topic><toplevel>online_resources</toplevel><creatorcontrib>Glattauer, Robin</creatorcontrib><creatorcontrib>Frühwirth, Rudolf</creatorcontrib><creatorcontrib>Lettenbichler, Jakob</creatorcontrib><creatorcontrib>Mitaroff, Winfried</creatorcontrib><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science &amp; Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>Access via ProQuest (Open Access)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Glattauer, Robin</au><au>Frühwirth, Rudolf</au><au>Lettenbichler, Jakob</au><au>Mitaroff, Winfried</au><format>book</format><genre>document</genre><ristype>GEN</ristype><atitle>Forward Tracking in the ILD Detector</atitle><jtitle>arXiv.org</jtitle><date>2012-02-13</date><risdate>2012</risdate><eissn>2331-8422</eissn><abstract>The reconstruction software for ILD is currently subject to a major revision, aiming at improving its accuracy, speed, efficiency and maintainability in time for the upcoming DBD Report. This requires replacing old code by novel methods for track search and fit, together with modern standards for interfaces and tools. Track reconstruction in the "forward region", defined by the silicon Forward Tracking Detector (FTD), relies heavily on a powerful stand-alone track search. The new software makes use of a Cellular Automaton, a Kalman filter, and a Hopfield Neural Network. We give an overview of the project, its methods and merits.</abstract><cop>Ithaca</cop><pub>Cornell University Library, arXiv.org</pub><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier EISSN: 2331-8422
ispartof arXiv.org, 2012-02
issn 2331-8422
language eng
recordid cdi_proquest_journals_2085862467
source Freely Accessible Journals
subjects Cellular automata
Kalman filters
Maintainability
Neural networks
Reconstruction
Software
Tracking
title Forward Tracking in the ILD Detector
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-14T11%3A21%3A46IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=document&rft.atitle=Forward%20Tracking%20in%20the%20ILD%20Detector&rft.jtitle=arXiv.org&rft.au=Glattauer,%20Robin&rft.date=2012-02-13&rft.eissn=2331-8422&rft_id=info:doi/&rft_dat=%3Cproquest%3E2085862467%3C/proquest%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2085862467&rft_id=info:pmid/&rfr_iscdi=true