Using evolutionary algorithms to extract field theory mass spectra

TL;DR

This paper presents a novel application of evolutionary algorithms to accurately extract particle mass spectra from lattice QCD simulations by optimizing fits across multiple datasets.

Contribution

It introduces the use of evolutionary algorithms for globally optimizing fits with variable states, improving the analysis of lattice QCD mass spectra.

Findings

Evolutionary algorithms effectively find global solutions for mass spectrum extraction.

The method handles multiple datasets and variable state numbers.

Improved accuracy in identifying particle masses from lattice QCD data.

Abstract

The spectrum of masses from a lattice QCD simulation may be found by fitting exponential functions to correlators of operators possessing the quantum numbers of the particles of interest. The ability of evolutionary algorithms to find globally optimized solutions containing a variable number of states across multiple data sets is exploited to provide a promising solution to the problem of finding these fits.