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dc.contributor.authorŻarnecki , Aleksander Filip
dc.contributor.authorPiotrowski , Lech Wiktor
dc.contributor.authorMankiewicz , Lech
dc.contributor.authorMałek , Sebastian
dc.date.accessioned2017-04-20T08:30:17Z
dc.date.available2017-04-20T08:30:17Z
dc.date.issued2013
dc.identifier.citationActa Polytechnica. 2013, vol. 53, no. 1.
dc.identifier.issn1210-2709 (print)
dc.identifier.issn1805-2363 (online)
dc.identifier.urihttp://hdl.handle.net/10467/67846
dc.description.abstractThe Luiza analysis framework for GLORIA is based on the Marlin package, which was originally developed for data analysis in the new High Energy Physics (HEP) project, International Linear Collider (ILC). The HEP experiments have to deal with enormous amounts of data and distributed data analysis is therefore essential. The Marlin framework concept seems to be well suited for the needs of GLORIA. The idea (and large parts of the code) taken from Marlin is that every computing task is implemented as a processor (module) that analyzes the data stored in an internal data structure, and the additional output is also added to that collection. The advantage of this modular approach is that it keeps things as simple as possible. Each step of the full analysis chain, e.g. from raw images to light curves, can be processed step-by-step, and the output of each step is still self consistent and can be fed in to the next step without any manipulation.en
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherČeské vysoké učení technické v Prazecs
dc.publisherCzech Technical University in Pragueen
dc.relation.ispartofseriesActa Polytechnica
dc.relation.urihttps://ojs.cvut.cz/ojs/index.php/ap/article/view/1718
dc.rightsCreative Commons Attribution 4.0 International Licenseen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectTelescope networken
dc.subjectimage processingen
dc.subjectdata analysisen
dc.titleLuiza: Analysis Framework for GLORIA
dc.typearticleen
dc.date.updated2017-04-20T08:30:17Z
dc.rights.accessopenAccess
dc.type.statusPeer-reviewed
dc.type.versionpublishedVersion


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Creative Commons Attribution 4.0 International License
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