English

Efficient and scalable Path Integral Monte Carlo Simulations with worm-type updates for Bose-Hubbard and XXZ models

Statistical Mechanics 2022-10-03 v3 Computational Physics

Abstract

We present a novel and open-source implementation of the worm algorithm, which is an algorithm to simulate Bose-Hubbard and sign-positive spin models using a path integral representation of the partition function. The code can deal with arbitrary lattice structures and assumes spin-exchange terms, or bosonic hopping amplitudes, between nearest-neighbor sites, and local or nearest-neighbor interactions of the density-density type. We explicitly demonstrate the near-linear scaling of the algorithm with respect to the system volume and the inverse temperature and analyze the autocorrelation times in the vicinity of a U(1) second order phase transition. The code is written in such a way that extensions to other lattice models as well as closely-related sign-positive models can be done straightforwardly on top of the provided framework.

Keywords

Cite

@article{arxiv.2204.12262,
  title  = {Efficient and scalable Path Integral Monte Carlo Simulations with worm-type updates for Bose-Hubbard and XXZ models},
  author = {Nicolas Sadoune and Lode Pollet},
  journal= {arXiv preprint arXiv:2204.12262},
  year   = {2022}
}

Comments

21 pages, 8 figures; open source code available under https://github.com/LodePollet/worm