Electromagnetic and weak structure of the nucleon studied within Bayesian neural network methods

Our project focused on developing Bayesian neural network methods for studying the nucleon’s electroweak structure. This approach reduced the dependence of the analysis on model assumptions and enabled a more reliable extraction of physical observables. The work led to new parametrizations of electromagnetic and axial form factors, studies of two-photon exchange effects, comparisons with quantum field-theoretical calculations, and a Bayesian determination of the proton charge radius.

Beyond the scientific publications, the project also led to the development of a dedicated BNN C++ library, written from scratch by K. Graczyk and C. Juszczak.

Funding: [place for funding information]

References:
JHEP 09, 053 (2010)
Phys. Rev. C 84, 034314 (2011)
Phys. Rev. C 88, 065205 (2013)
Phys. Rev. C 90, 054334 (2014)
J. Phys. G 42, 034019 (2015)
PoS NuFACT2018 (2019) 101
Phys. Rev. C 99, 025204 (2019)

Collaborators: Cezary Juszczak, Robert Sulej, Piotr Płoński, Luis Alvarez-Ruso, Eduardo Saul-Sal