Truncated Partial-Wave Analysis for $\eta$-photoproduction observables via Bayesian Statistics

TL;DR

This paper applies Bayesian statistics to truncated partial-wave analysis of $ ext{eta}$-photoproduction, exploring ambiguities and predicting unmeasured observables to guide future experiments.

Contribution

It introduces the first combination of Bayesian methods with truncated partial-wave analysis to analyze ambiguities in $ ext{eta}$-photoproduction data.

Findings

Bayesian analysis reveals structure of ambiguities in partial-wave solutions.

Predictions for unmeasured polarization observables to guide future experiments.

Identification of promising measurements to resolve remaining ambiguities.

Abstract

A truncated partial-wave analysis is performed for $\eta$-photoproduction using the polarization observables $\sigma_0, \Sigma, T, E, F$ and $G$. Different truncation orders are analyzed for six energy bins within the range of $E^{lab}_{\gamma} \in [750, 1250]$ MeV. Bayesian statistics is combined with truncated partial-wave analysis for the first time to investigate the structure of emerging ambiguities and their relevance in comparison to each other. Marginal distributions for the electromagnetic multipole parameters are presented together with predictions for polarization observables which have not yet been measured, in order to determine promising future measurements able to remove remaining mathematical ambiguities.