Testing Algorithms for Finite Temperature Lattice QCD

TL;DR

This paper reviews recent algorithmic improvements for simulating finite temperature QCD on a lattice, focusing on the Rational Hybrid Monte Carlo method and various speed-up techniques to enhance efficiency and accuracy.

Contribution

It introduces the application of the RHMC algorithm with multiple speed-up strategies for finite temperature lattice QCD simulations, improving upon previous methods.

Findings

RHMC is reversible and allows a Metropolis accept/reject step.

Multiple time scales and efficient integrators speed up simulations.

Hasenbusch pre-conditioning reduces fermion force computational cost.

Abstract

We discuss recent algorithmic improvements in simulating finite temperature QCD on a lattice. In particular, the Rational Hybrid Monte Carlo(RHMC) algorithm is employed to generate lattice configurations for 2+1 flavor QCD. Unlike the Hybrid R Algorithm, RHMC is reversible, admitting a Metropolis accept/reject step that eliminates the $\mathcal{O}(\delta t^2)$ errors inherent in the R Algorithm. We also employ several algorithmic speed-ups, including multiple time scales, the use of a more efficient numerical integrator, and Hasenbusch pre-conditioning of the fermion force.