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Machine learning approaches for parameter reweighting in MC samples of top quark production in CMS
In particle physics, Monte Carlo (MC) event generators are needed to compare theory to the measured data. Many MC samples have to be generated to account for theoretical systematic uncertainties, at a significant computational cost. Therefore, the MC statistic becomes a limiting factor for most meas...
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| Lenguaje: | eng |
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2023
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| Acceso en línea: | http://cds.cern.ch/record/2860873 |