Neural network parameterizations of electromagnetic nucleon form-factors

作者：Graczyk Krzysztof M^*; Plonski Piotr; Sulej Robert

来源：The Journal of High Energy Physics, 2010, 2010(9): 053.

DOI：10.1007/JHEP09(2010)053

• Lepton-Nucleon Scattering

The electromagnetic nucleon form-factors data are studied with artificial feed forward neural networks. As a result the unbiased model-independent form-factor parametrizations are evaluated together with uncertainties. The Bayesian approach for the neural networks is adapted for chi(2) error-like function and applied to the data analysis. The sequence of the feed forward neural networks with one hidden layer of units is considered. The given neural network represents a particular form-factor parametrization. The so-called evidence (the measure of how much the data favor given statistical model) is computed with the Bayesian framework and it is used to determine the best form factor parametrization.

• 出版日期2010-9