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International Journal of Modern Physics C

A NONLOCAL APPROACH TO VERTEX MODELS AND QUANTUM SPIN SYSTEMS

Hans Gerd Evertz, MIHAI MARCU

Published Dec 1, 1993• 1 citation
Publisher

Abstract

We discuss the loop-algorithm, a new type of cluster algorithm that reduces critical slowing down in vertex models and in quantum spin systems. We cover the example of the 6-vertex model in detail. For the F-model, we present numerical results that demonstrate the effectiveness of the loop algorithm. We show how to modify the original algorithm for some more complicated situations, especially for quantum spin systems in one and two dimensions, and we discuss parallelization.

DOI
10.1142/s0129183193000902

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We discuss the loop-algorithm, a new type of cluster algorithm that reduces critical slowing down in vertex models and in quantum spin systems. We cover the example of the 6-vertex model in detail. For the F-model, we present numerical results that demonstrate the effectiveness of the loop algorithm. We show how to modify the original algorithm for some more complicated situations, especially for quantum spin systems in one and two dimensions, and we discuss parallelization.
We present a new type of cluster algorithm that strongly reduces critical slowing down in simulations of vertex models. Since the clusters are closed paths of bonds, we call it the loop algorithm. The basic steps in constructing a cluster are the breakup and the freezing of vertices. We concentrate on the case of the F model, which is a subset of the six-vertex model exhibiting a Kosterlitz-Thouless transition. The loop algorithm is also applicable to simulations of other vertex models and of one- and two-dimensional quantum spin systems.
We present the loop algorithm, a new type of cluster algorithm that we recently introduced for the F model. Using the framework of Kandel and Domany, we show how to generalize the algorithm to the arrow flip symmetric 6 vertex model. We propose the principle of least possible freezing as the guide to choosing the values of free parameters in the algorithm. Finally, we briefly discuss the application of our algorithm to simulations of quantum spin systems. In particular, all necessary information is provided for the simulation of spin 1 2 models. 1.
Cluster algorithms are developed for simulating quantum spin systems like the one- and two-dimensional Heisenberg ferro- and anti-ferromagnets. The corresponding two- and three-dimensional classical spin models with four-spin couplings are maped to blockspin models with two-blockspin interactions. Clusters of blockspins are updated collectively. The efficiency of the method is investigated in detail for one-dimensional spin chains. Then in most cases the new algorithms solve the problems of slowing down from which standard algorithms are suffering. Two-dimensional quantum spin systems are relevant for the description of the undoped anti-ferromagnetic precursor insulators of high-Tc superconductors. Presumably understanding the physics of the superconductors requires an understanding of their precursor insulators. This already is a nontrivial problem, which most likely does not allow for a complete analytic solution. Therefore it is natural to use a numerical approach to compute the properties of these materials. At present different
We apply a meron cluster algorithm to the XY spin chain, which describes a quantum rotor. This is a multi-cluster simulation supplemented by an improved estimator, which deals with objects of half-integer topological charge. This method is powerful enough to provide precise results for the model with a θ-term — it is therefore one of the rare examples, where a system with a complex action can be solved numerically. In particular we measure the correlation length, as well as the topological and magnetic susceptibility. We discuss the algorithmic efficiency in view of the critical slowing down. Due to the excellent performance that we observe, it is strongly motivated to work on new applications of meron cluster algorithms in higher dimensions.