Comparison of neural network and hadronic model predictions of the two-photon exchange effect

Predictions for the two-photon exchange (TPE) correction to the unpolarized ep elastic cross section, obtained within two different approaches, are confronted and discussed in detail. In the first one the TPE correction is extracted from experimental data by applying the Bayesian neural network statistical framework. In the other the TPE is given by box diagrams, with the nucleon and the P-33 resonance as the hadronic intermediate states. Two different form factor parametrizations for both the proton and the P-33 resonance are taken into consideration. Proton form factors are obtained from the global fit of the full model (with the TPE correction) to the unpolarized cross-section data. Predictions of the two methods agree well in the intermediate Q(2) range of 1-3 GeV2. Above Q(2) = 3 GeV2 the agreement is at the 2 sigma level. Below Q(2) = 1 GeV2 the consistency between the two approaches is broken. The values of the proton radius extracted within the models are given. In both cases predictions for the VEPP-3 experiment have been obtained and confronted with the preliminary experimental results.