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Treatment and Combination of Data Quality Monitoring Histograms to Perform Data vs. Monte Carlo Validation

In CMS's automated data quality validation infrastructure, it is not currently possible to assess how well Monte Carlo simulations describe data from collisions, if at all. In order to guarantee high quality data, a novel work flow was devised to perform `data vs. Monte Carlo' validation....

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Detalles Bibliográficos
Autor principal: Colin, Nolan
Lenguaje:eng
Publicado: 2013
Materias:
Acceso en línea:http://cds.cern.ch/record/1610155
Descripción
Sumario:In CMS's automated data quality validation infrastructure, it is not currently possible to assess how well Monte Carlo simulations describe data from collisions, if at all. In order to guarantee high quality data, a novel work flow was devised to perform `data vs. Monte Carlo' validation. Support for this comparison was added by allowing distributions from several Monte Carlo samples to be combined, matched to the data and then displayed in a histogram stack, overlaid with the experimental data.