Testing trivializing maps in the Hybrid Monte Carlo algorithm

Abstract

We test a recent proposal to use approximate trivializing maps in a field theory to speed up Hybrid Monte Carlo simulations. Simulating the CP^{N-1} model, we find a small improvement with the leading order transformation, which is however compensated by the additional computational overhead. The scaling of the algorithm towards the continuum is not changed. In particular, the effect of the topological modes on the autocorrelation times is studied.

18 pages, 7 figures

References in corpus (2)

• Critical slowing down and error analysis in lattice QCD simulations
• Topology, the Wilson flow and the HMC algorithm

Cited by in corpus (12)

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• Metadynamics Surfing on Topology Barriers: the $C{P}^{N-1}$ Case
• Learning Trivializing Gradient Flows for Lattice Gauge Theories
• Status and challenges of simulations with dynamical fermions
• Parallel Tempered Metadynamics: Overcoming potential barriers without surfing or tunneling
• Precision study of critical slowing down in lattice simulations of the CP^{N-1} model
• Fighting topological freezing in the two-dimensional CP${}^{N-1}$ model
• Scaling flow-based approaches for topology sampling in $\mathrm{SU}(3)$ gauge theory