Bayesian inference of the resonance content of p(gamma,K+)Lambda
Pieter Vancraeyveld, Lesley De Cruz, Jan Ryckebusch, Tom Vrancx
TL;DR
This paper applies Bayesian inference within a Regge-plus-resonance framework to analyze p(gamma,K+)Lambda data, identifying the most probable nucleon resonances, especially around 1900 MeV, by evaluating thousands of model variants.
Contribution
It introduces a comprehensive Bayesian approach to determine resonance content in kaon photoproduction, considering all combinations of candidate resonances up to spin 5/2.
Findings
Identified the best model RPR-2011 for resonance analysis.
Highlighted the significance of nucleon resonances near 1900 MeV.
Evaluated 2048 model variants to robustly determine resonance contributions.
Abstract
A Bayesian analysis of the world's p(gamma,K+)Lambda data is presented. We adopt a Regge-plus-resonance framework featuring consistent couplings for nucleon resonances up to spin J=5/2, and evaluate 2048 model variants considering all possible combinations of 11 candidate resonances. The best model, labeled RPR-2011, is discussed with special emphasis on nucleon resonances in the 1900-MeV mass region.
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