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Analysis Preservation and Systematic Reinterpretation within the ATLAS Experiment

The LHC data analysis software used in order to derive and publish experimental results is an important asset that is necessary to preserve in order to fully exploit the scientific potential of a given measurement. Among others, important use cases of analysis preservation are the reproducibility of...

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Detalles Bibliográficos
Autores principales: Heinrich, Lukas, Cranmer, Kyle
Lenguaje:eng
Publicado: 2017
Materias:
Acceso en línea:http://cds.cern.ch/record/2280505
Descripción
Sumario:The LHC data analysis software used in order to derive and publish experimental results is an important asset that is necessary to preserve in order to fully exploit the scientific potential of a given measurement. Among others, important use cases of analysis preservation are the reproducibility of the original results and the reusability of the analysis procedure in the context of new scientific studies. A prominent use-case for the latter is the systematic reinterpretation of searches for new Physics in terms of signal models that not studied in the original publication (RECAST). This paper presents the usage of the graph-based workflow description language yadage to drive the reinterpretation of preserved HEP analyses. The analysis software for individual states in the analysis is preserved using Docker containers, while the workflow structure is preserved using plain JSON documents. This allows the re-execution of complex analysis workflows on industry standard container-based distributed computing clusters (Kubernetes via OpenStack Magnum) We present re-interpretations of ATLAS analyses based on both the original ATLAS analysis code and third-party re-implementations such as CheckMATE and integrations with other analysis preservation efforts such as the CERN Analysis Preservation Portal.