Speaker
Dr
Sahibjeet Singh
(Brookhaven National Laboratory (US))
Description
With the LHC transitioning to a precision measurement machine, the proton Parton Distribution Functions (PDFs) are becoming a leading source of uncertainty in analyses such as the measurements of top quark mass or the Higgs boson width. Furthermore, the high-momentum-fraction (high-x) regime is of particular interest when probing the most energetic collisions at the LHC. Thus, it is crucial to understand and potentially reduce the PDF uncertainties in this regime. Using machine learning techniques, we construct a discriminant sensitive to the gluon PDF in the high-x regime, to be used in future PDF fits.
Authors
BinBin Dong
(Michigan State University (US))
Mr
Jarrett Fein
(Michigan State University (US))
Jason P. Gombas
(Michigan State University (US))
Reinhard Schwienhorst
(Michigan State University (US))
Dr
Sahibjeet Singh
(Brookhaven National Laboratory (US))
