Bayesian inference of the resonance content of p(gamma,K^+)Lambda

TL;DR

This paper employs Bayesian inference within a Regge-plus-resonance framework to identify the most probable nucleon resonances contributing to the p(gamma,K^+)Lambda reaction, based on a comprehensive analysis of global experimental data.

Contribution

It introduces a Bayesian approach to select the most likely resonance contributions among 11 candidates, using Bayesian evidence to evaluate 2048 model variants.

Findings

Identified key resonances with highest probability: S11(1535), S11(1650), F15(1680), P13(1720), D13(1900), P13(1900), P11(1900), F15(2000)

Selected the best model out of 2048 variants based on Bayesian evidence

Demonstrated the effectiveness of Bayesian model comparison in hadronic reaction analysis.

Abstract

A Bayesian analysis of the world's p(gamma,K^+)Lambda data is presented. From the proposed selection of 11 resonances, we find that the following nucleon resonances have the highest probability of contributing to the reaction: S11(1535), S11(1650), F15(1680), P13(1720), D13(1900), P13(1900), P11(1900), and F15(2000). We adopt a Regge-plus-resonance framework featuring consistent couplings for nucleon resonances up to spin J=5/2. We evaluate all possible combinations of 11 candidate resonances. The best model is selected from the 2048 model variants by calculating the Bayesian evidence values against the world's p(gamma,K^+)Lambda data.