21-25 August 2017
University of Washington, Seattle
US/Pacific timezone

NNPDF: Neural Networks for precision PDF determinations

21 Aug 2017, 17:20
20m
106 (Alder Hall)

106

Alder Hall

Oral Track 3: Computations in Theoretical Physics: Techniques and Methods Track 3: Computations in Theoretical Physics: Techniques and Methods

Speaker

Stefano Carrazza (CERN)

Description

Parton Distribution Functions (PDFs) are a crucial ingredient for accurate and reliable theoretical predictions for precision phenomenology at the LHC.
The NNPDF approach to the extraction of Parton Distribution Functions relies on Monte Carlo techniques and Artificial Neural Networks to provide an unbiased determination of parton densities with a reliable determination of their uncertainties.
I will discuss the NNPDF methodology in general, the latest NNPDF global fit (NNPDF3.1) and then present ideas to improve the training methodology used in the NNPDF fits.

Primary authors

Dr Alberto Guffanti (Università degli Studi di Torino) Stefano Carrazza (CERN)

Presentation materials

Peer reviewing

Paper