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Lesley De Cruz, Jan Ryckebusch, Tom Vrancx, Pieter Vancraeyveld
 

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Abstract 

We address the issue of unbiased model selection and propose a methodology based on Bayesian inference to extract physical information from kaon photoproduction γp→K+Λ data. We use the single-channel Regge-plus-resonance (RPR) framework for γp→K+Λ to illustrate the proposed strategy. The Bayesian evidence Z is a quantitative measure for the model's fitness given the world's data. We present a numerical method for performing the multidimensional integrals in the expression for the Bayesian evidence. We use the γp→K+Λ data with an invariant energy W>2.6 GeV in order to constrain the background contributions in the RPR framework with Bayesian inference. Next, the resonance information is extracted from the analysis of differential cross sections and single- and double-polarization observables. This background and resonance content constitutes the basis of a model, which is coined RPR-2011. It is shown that RPR-2011 yields a comprehensive account of the kaon photoproduction data and provides reasonable predictions for e+p→e′+K++Λ observables.

Reference 
 
 
DOI