Minimal Autocorrelation in Hybrid Monte Carlo simulations using Exact Fourier Acceleration

Fuente: arXiv
Enregistré dans:
Détails bibliographiques
Auteurs principaux: Ostmeyer, Johann, Buividovich, Pavel
Format: Preprint
Publié: 2024
Sujets:
Accès en ligne:
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
_version_ 1866918010012303360
author Ostmeyer, Johann
Buividovich, Pavel
author_facet Ostmeyer, Johann
Buividovich, Pavel
contents The hybrid Monte Carlo (HMC) algorithm is a ubiquitous method in computational physics with applications ranging from condensed matter to lattice QCD and beyond. However, HMC simulations often suffer from long autocorrelation times, severely reducing their efficiency. In this work two of the main sources of autocorrelations are identified and eliminated. The first source is the sampling of the canonical momenta from a sub-optimal normal distribution, the second is a badly chosen trajectory length. Analytic solutions to both problems are presented and implemented in the exact Fourier acceleration (EFA) method. It completely removes autocorrelations for near-harmonic potentials and consistently yields (close-to-) optimal results for numerical simulations of the Su-Schrieffer-Heeger and the Ising models as well as in lattice gauge theory, in some cases reducing the autocorrelation by multiple orders of magnitude. EFA is advantageous for and easily applicable to any HMC simulation of an action that includes a quadratic part.
format Preprint
id arxiv_https___arxiv_org_abs_2404_09723
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Minimal Autocorrelation in Hybrid Monte Carlo simulations using Exact Fourier Acceleration
Ostmeyer, Johann
Buividovich, Pavel
High Energy Physics - Lattice
Strongly Correlated Electrons
Computational Physics
The hybrid Monte Carlo (HMC) algorithm is a ubiquitous method in computational physics with applications ranging from condensed matter to lattice QCD and beyond. However, HMC simulations often suffer from long autocorrelation times, severely reducing their efficiency. In this work two of the main sources of autocorrelations are identified and eliminated. The first source is the sampling of the canonical momenta from a sub-optimal normal distribution, the second is a badly chosen trajectory length. Analytic solutions to both problems are presented and implemented in the exact Fourier acceleration (EFA) method. It completely removes autocorrelations for near-harmonic potentials and consistently yields (close-to-) optimal results for numerical simulations of the Su-Schrieffer-Heeger and the Ising models as well as in lattice gauge theory, in some cases reducing the autocorrelation by multiple orders of magnitude. EFA is advantageous for and easily applicable to any HMC simulation of an action that includes a quadratic part.
title Minimal Autocorrelation in Hybrid Monte Carlo simulations using Exact Fourier Acceleration
topic High Energy Physics - Lattice
Strongly Correlated Electrons
Computational Physics
url https://arxiv.org/abs/2404.09723