Speaker
Nicholas Hunt-Smith
Description
We review various methods used to estimate uncertainties in parton distribution functions (PDFs), finding that utilizing a neural network on a simplified example of PDF data has the potential to inflate uncertainties.
Author
Co-authors
Alberto Accardi
(Hampton U. and Jefferson Lab)
Anthony Thomas
Martin John White
(University of Adelaide (AU))
Wally Melnitchouk
(Jefferson Lab)
nobuo sato
(jlab)