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Making RooFit Ready for Run 3

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arxiv 2003.12861 v1 pith:6WLM4WJQ submitted 2020-03-28 cs.MS hep-exphysics.data-an

Stephan Hageboeck , Lorenzo Moneta This is my paper · ORCID
classification cs.MShep-exphysics.data-an
keywords roofitdatawillcomplexitydatasetsenablelargelarger
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RooFit and RooStats, the toolkits for statistical modelling in ROOT, are used in most searches and measurements at the Large Hadron Collider. The data to be collected in Run 3 will enable measurements with higher precision and models with larger complexity, but also require faster data processing. In this work, first results on modernising RooFit's collections, restructuring data flow and vectorising likelihood fits in RooFit will be discussed. These improvements will enable the LHC experiments to process larger datasets without having to compromise with respect to model complexity, as fitting times would increase significantly with the large datasets to be expected in Run 3.

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Cited by 1 Pith paper

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  1. Tracking Paths in Planar Graphs

    cs.DM 2019-08 conditional novelty 6.0 of 10

    Tracking paths is NP-complete on planar graphs, admits a 4-approximation, and is linear-time solvable on bounded clique-width graphs with a given decomposition.

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