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Advancements in the KATRIN Analysis Framework for Neutrino Mass Measurement

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The KATRIN Experiment, focusing on the model-independent measurement of the absolute neutrino mass scale, aims for unprecedented sensitivity of 0.2 eV/c². With a collaboration of 130 scientists across 5 countries, the framework optimizes data acquisition and control through a service-oriented architecture. Highlights include integrated data processing, real-time monitoring, and automated quality checks. The framework facilitates both online and offline analysis, ensuring reliable access to heterogeneously distributed data while maintaining stability and performance.

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Advancements in the KATRIN Analysis Framework for Neutrino Mass Measurement

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  1. The KATRIN Analysis Framework 2ndASPERA Workshop on Computing and Astroparticle Physics Barcelona 2011

  2. Outline • The KATRIN Experiment • Data Taking and Experiment Control • The Analysis Software Framework • Implementation Details • Conclusion & Outlook Marco Haag – The KATRIN Analysis Framework

  3. The Karlsruhe TRItiumNeutrino (KATRIN) Experiment • Experimental objective: • model-independent measurementofthe absolute neutrinomassscale • sensitivity: 0.2 eV/c² (90% C.L.) • source: gaseoustritium (ß-decay) • Collaboration • 130 scientists • 5 countries • 13 institutions Marco Haag – The KATRIN Analysis Framework

  4. β-decayandneutrinomass • Directkinematicmeasurementoftheeffectiveneutrinomass • Tritium asβ-emitter • MAC-E filter (electrostaticfilterwithmagneticadibaticcollimation) asspectrometer • Data rate: mHz - kHz Marco Haag – The KATRIN Analysis Framework

  5. Experiment Control & Data Taking Marco Haag – The KATRIN Analysis Framework

  6. Requirements • DAQ: around 1 GB per day • SlowControl: Large numberofheterogenouslydistributedsensors,ca. 10.000 channels • Calibration, geometryinformation, simulationresults, … • Constant monitoringisnecessarytomaintainhighlystableoperatingconditionsoveryears. • The neutrinomasssensitivitygoalof 0.2 eV/c2demandsmanyparameterstobereliablyknown on the ppm (10-6) level. • Data hastoberestructured, calibratedandmergedfrommany different sources, evenfor simple analysistasks. Marco Haag – The KATRIN Analysis Framework

  7. Conventional file-baseddataaccessis not feasable: Marco Haag – The KATRIN Analysis Framework

  8. Marco Haag – The KATRIN Analysis Framework

  9. Service OrientedArchitectureat KATRIN • ADEI (Advanced Data Extraction Interface) • SlowControl data processing and caching • PHP based web platform for online data access Marco Haag – The KATRIN Analysis Framework

  10. Service OrientedArchitectureat KATRIN • KATRIN Data Manager • C++ WebService (Apache Webserver / FastCGI) • RPC (remote procedure call) interface andXML Binding with gSOAP 2.8 • Widget-centric C++ WebToolkitWtfor interactive web development • SQL database access through ORM (object relational mapping) abstraction layer Wt::Dbo Marco Haag – The KATRIN Analysis Framework

  11. Service OrientedArchitectureat KATRIN • Client C++ KATRIN Library KALI • Basic utility functions (XML binding, exception handling, logging, …) • Data retrieval and upload throughRPC programming interface • Common constants and data types • ROOT (CERN) support Marco Haag – The KATRIN Analysis Framework

  12. Service OrientedArchitectureat KATRIN Marco Haag – The KATRIN Analysis Framework

  13. The Benefitsof a Service OrientedApproach • Well defined data flow and server-side processing(unnecessary data transfer is minimized) • Automated data quality and integrity checks • Central versionanduseraccesscontrol • Reliabletransactionhandling • Data access through intuitive and consistent programming interfaces • Standardized code, common constants and data formats • Server-sidedataprocessingisperformedbyonlyfew maintainable services • Consistent set of clientapplications (analysisandsimulation) speaking a „similarlanguage“ Marco Haag – The KATRIN Analysis Framework

  14. Offline Analysis Marco Haag – The KATRIN Analysis Framework

  15. Online Analysis (Browser Screenshot) External PHP application (ADEI) accessing KATRIN DAQ datathrough PHP-SOAP. (Plugindevelopedby Sebastian Vöcking, University of Münster) Marco Haag – The KATRIN Analysis Framework

  16. Online Analysis (Browser Screenshot) Combined SlowControl and DAQ data: Pixel detector hit rate over electron gun voltage. Marco Haag – The KATRIN Analysis Framework

  17. Summary & Conclusion • C++ web servicewith SOAP interfacesforclientapplicationsimplementedandtested • Standardized RPC interfaces (remote functioncalls) nowallow intuitive accesstoheterogeneously distributed and structured data • Automateddataprocessingandcachingestablished • First stabilityandperformancetestlookvery promising • Preliminary online analysistoolsavailable • Deployable C++ clientlibraryfor offline analysesofmainspectrometercommissioningmeasurementsbythe end of 2011 Marco Haag – The KATRIN Analysis Framework

  18. Thankyouforyourattention. n n n n n n n Marco Haag – The KATRIN Analysis Framework

  19. References and URLs • The KATRIN Experiment:http://www-ik.fzk.de/tritium • ADEI:http://dside.dyndns.org/adei • Orca:http://orca.physics.unc.edu/~markhowe/Orca_Help • gSoap:http://www.cs.fsu.edu/~engelen/soap.html • Wt:http://www.webtoolkit.eu Marco Haag – The KATRIN Analysis Framework

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