Testing algorithms for critical slowing down

Abstract

We present the preliminary tests on two modifications of the Hybrid Monte Carlo (HMC) algorithm. Both algorithms are designed to travel much farther in the Hamiltonian phase space for each trajectory and reduce the autocorrelations among physical observables thus tackling the critical slowing down towards the continuum limit. We present a comparison of costs of the new algorithms with the standard HMC evolution for pure gauge fields, studying the autocorrelation times for various quantities including the topological charge.

8 pages, 2 figures, Lattice 2017 conference proceedings

References in corpus (4)

• Critical slowing down and error analysis in lattice QCD simulations
• Exploring the HMC trajectory-length dependence of autocorrelation times in lattice QCD
• Diffusion of topological charge in lattice QCD simulations
• Non-renormalizability of the HMC algorithm

Cited by in corpus (6)

• Flow-based generative models for Markov chain Monte Carlo in lattice field theory
• Nuclear matrix elements from lattice QCD for electroweak and beyond-Standard-Model processes
• Deep-learning quasi-particle masses from QCD equation of state
• Scaling properties of multiscale equilibration
• Parallel Tempered Metadynamics: Overcoming potential barriers without surfing or tunneling
• Extended framework for the hybrid Monte Carlo in lattice gauge theory