Two-photon exchange effect studied with neural networks
- Institute of Theoretical Physics, University of Wroclaw, pl. M. Borna 9, PL-50-204 Wroclaw (Poland)
An approach to the extraction of the two-photon exchange (TPE) correction from elastic ep scattering data is presented. The cross-section, polarization transfer (PT), and charge asymmetry data are considered. It is assumed that the TPE correction to the PT data is negligible. The form factors and TPE correcting term are given by one multidimensional function approximated by the feedforward neural network (NN). To find a model-independent approximation, the Bayesian framework for the NNs is adapted. A large number of different parametrizations is considered. The most optimal model is indicated by the Bayesian algorithm. The obtained fit of the TPE correction behaves linearly in {epsilon} but it has a nontrivial Q{sup 2} dependence. A strong dependence of the TPE fit on the choice of parametrization is observed.
- OSTI ID:
- 21596745
- Journal Information:
- Physical Review. C, Nuclear Physics, Vol. 84, Issue 3; Other Information: DOI: 10.1103/PhysRevC.84.034314; (c) 2011 American Institute of Physics; Country of input: International Atomic Energy Agency (IAEA); ISSN 0556-2813
- Country of Publication:
- United States
- Language:
- English
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Related Subjects
APPROXIMATIONS
ASYMMETRY
COMPUTERIZED SIMULATION
CORRECTIONS
CROSS SECTIONS
ELASTIC SCATTERING
ELECTRON-PROTON INTERACTIONS
EXTRACTION
FORM FACTORS
NEURAL NETWORKS
PHOTONS
POLARIZATION
BOSONS
CALCULATION METHODS
DIMENSIONLESS NUMBERS
ELECTRON-NUCLEON INTERACTIONS
ELEMENTARY PARTICLES
INTERACTIONS
LEPTON-BARYON INTERACTIONS
LEPTON-HADRON INTERACTIONS
LEPTON-NUCLEON INTERACTIONS
MASSLESS PARTICLES
PARTICLE INTERACTIONS
PARTICLE PROPERTIES
SCATTERING
SEPARATION PROCESSES
SIMULATION