Improved Sampling Algorithms in Lattice QCD

TL;DR

This paper explores advanced sampling algorithms based on Reverse Monte Carlo techniques to improve efficiency in lattice QCD simulations, particularly addressing critical slowing down in topological charge evolution.

Contribution

It introduces novel RMC-inspired algorithms tailored for pure gauge theory, demonstrating their potential to enhance sampling efficiency in lattice QCD.

Findings

Reduced autocorrelation times for topological charge

Improved exploration of configuration space

Potential to mitigate critical slowing down

Abstract

Reverse Monte Carlo (RMC) is an algorithm that incorporates stochastic modification of the action as part of the process that updates the fields in a Monte Carlo simulation. Such update moves have the potential of lowering or eliminating potential barriers that may cause inefficiencies in exploring the field configuration space. The highly successful Cluster algorithms for spin systems can be derived from the RMC framework. In this work we apply RMC ideas to pure gauge theory, aiming to alleviate the critical slowing down observed in the topological charge evolution as well as other long distance observables. We present various formulations of the basic idea and report on our numerical experiments with these algorithms.