Properties of Nucleon Resonances by means of a Genetic Algorithm

TL;DR

This paper introduces a genetic algorithm-based optimization method to accurately determine properties of nucleon resonances within a realistic photo-pion production model, improving parameter estimation and model assessment.

Contribution

It demonstrates the application of a genetic algorithm for reliable parameter extraction and error analysis of nucleon resonances in a complex physical model.

Findings

Successful parameter estimation for $elta$(1230) resonance.

Challenges in analyzing less well-known $elta$(1700) resonance.

Identification of model weaknesses through optimization.

Abstract

We present an optimization scheme that employs a Genetic Algorithm (GA) to determine the properties of low-lying nucleon excitations within a realistic photo-pion production model based upon an effective Lagrangian. We show that with this modern optimization technique it is possible to reliably assess the parameters of the resonances and the associated error bars as well as to identify weaknesses in the models. To illustrate the problems the optimization process may encounter, we provide results obtained for the nucleon resonances $\Delta$(1230) and $\Delta$(1700). The former can be easily isolated and thus has been studied in depth, while the latter is not as well known experimentally.