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Machine learning approaches for parameter reweighting for MC samples of top quark production in CMS

In high-energy particle physics, complex Monte Carlo (MC) simulations are needed to compare theory predictions to measurable quantities. Many and large MC samples are needed to be generated to take into account all the systematics. Therefore, the MC statistics (and hence the MC modeling uncertainti...

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Detalles Bibliográficos
Autor principal: Guglielmi, Valentina
Lenguaje:eng
Publicado: 2022
Materias:
Acceso en línea:https://dx.doi.org/10.22323/1.414.1045
http://cds.cern.ch/record/2841031

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