Speaker
Dr
Ishara Fernando
(University of Virginia)
Description
Pseudo-data with simulated experimental errors can be generated to train an ensemble of Artificial Neural Networks (ANN) implemented on a regression to extract Transverse Momentum-dependent Distributions (TMDs). A preliminary analysis will be presented on the reliability in extraction of the Sivers function imposed in the pseudo-data given the bounds on the experimental errors, data sparsity, and complexity of phase-space.
Primary authors
Dr
Ishara Fernando
(University of Virginia)
Prof.
Dustin Keller
(University of Virginia)
Mr
Nicholas Newton
(University of Virginia)
