Graphical Representations and Worm Algorithms for the O($N$) Spin Model
Abstract
We present a family of graphical representations for the O() spin model, where represents the spin dimension, and corresponds to the Ising, XY and Heisenberg models, respectively. With an integer parameter , each configuration is the coupling of copies of subgraphs consisting of directed flows and copies of subgraphs constructed by undirected loops, which we call the XY and Ising subgraphs, respectively. On each lattice site, the XY subgraphs satisfy the Kirchhoff flow-conservation law and the Ising subgraphs obey the Eulerian bond condition. Then, we formulate worm-type algorithms and simulate the O() model on the simple-cubic lattice for from 2 to 6 at all possible . It is observed that the worm algorithm has much higher efficiency than the Metropolis method, and, for a given , the efficiency is an increasing function of . Beside Monte Carlo simulations, we expect that these graphical representations would provide a convenient basis for the study of the O() spin model by other state-of-the-art methods like the tensor network renormalization.
Keywords
Cite
@article{arxiv.2306.12218,
title = {Graphical Representations and Worm Algorithms for the O($N$) Spin Model},
author = {Longxiang Liu and Lei Zhang and Xiaojun Tan and Youjin Deng},
journal= {arXiv preprint arXiv:2306.12218},
year = {2023}
}
Comments
10 pages, 6 figures