Cargando…
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...
| Autor principal: | |
|---|---|
| Lenguaje: | eng |
| Publicado: |
2022
|
| Materias: | |
| Acceso en línea: | https://dx.doi.org/10.22323/1.414.1045 http://cds.cern.ch/record/2841031 |