Speaker
Prof.
Simonetta Liuti
(University of Virginia)
Description
I will discuss the application of an alternative type of neural network, the Self-Organizing Maps (SOMs), to extract parton distribution functions from various hard scattering processes. SOMs provide a complementary algorithm to NNPDFs yielding a parametrization that is free from the bias implicit in choosing specific analytic forms. At the same time it enables us to extrapolate to kinematical regions where data are not available.
I will show in particular the extraction using SOMs of the ratio d/u in the x=1 limit.
Primary author
Prof.
Simonetta Liuti
(University of Virginia)
