Towards the Minimal Spectrum of Excited Baryons

TL;DR

This paper introduces a method using penalized model selection techniques, specifically LASSO and BIC, to identify the minimal set of hyperon resonances needed to explain experimental data, overcoming traditional analysis limitations.

Contribution

It demonstrates a novel application of LASSO and BIC for blind identification of hyperon resonances in baryon reactions, reducing the complexity of resonance analysis.

Findings

Identified ten relevant hyperon resonances out of 21 candidates.

Compared different penalization schemes for resonance selection.

Showed the method's capability to determine relevant resonances among many candidates.

Abstract

In the light baryon sector resonances can be broad and overlapping and are in most cases not directly visible in the cross section data. Automatized model selection techniques that introduce penalties for resonances can be used to determine the minimally needed set of resonances to describe the data. Several possible penalization schemes are compared. As an application we perform a blindfold identification of hyperon resonances in the $\bar{K} N \to K \Xi$ reaction based on the Least Absolute Shrinkage and Selection Operator (LASSO) in combination with the Bayesian Information Criterion (BIC). We find ten resonances --- out of the 21 above-threshold hyperon resonances with spin $J\le 7/2$ listed by the Particle Data Group. In traditional analyses, it is practically impossible to test the relevance of all resonances and their combinations that may potentially contribute to the reaction. By contrast, the present method proves capable of determining the relevant resonances among a large pool of candidates.