Alet Fabien, Sørensen Erik S
Computational Laboratory, ETH Zürich, CH-8092 Zürich, Switzerland.
Phys Rev E Stat Nonlin Soft Matter Phys. 2003 Aug;68(2 Pt 2):026702. doi: 10.1103/PhysRevE.68.026702. Epub 2003 Aug 12.
We discuss the implementation of a directed geometrical worm algorithm for the study of quantum link-current models. In this algorithm the Monte Carlo updates are made through the biased reptation of a worm through the lattice. A directed algorithm is an algorithm where, during the construction of the worm, the probability for erasing the immediately preceding part of the worm, when adding a new part, is minimal. We introduce a simple numerical procedure for minimizing this probability. The procedure only depends on appropriately defined local probabilities and should be generally applicable. Furthermore, we show how correlation functions C(r,tau) can be straightforwardly obtained from the probability of a worm to reach a site (r,tau) away from its starting point independent of whether or not a directed version of the algorithm is used. Detailed analytical proofs of the validity of the Monte Carlo algorithms are presented for both the directed and undirected geometrical worm algorithms. Results for autocorrelation times and Green's functions are presented for the quantum rotor model.
我们讨论一种用于研究量子链电流模型的定向几何蠕虫算法的实现。在该算法中,蒙特卡罗更新是通过蠕虫在晶格中的有偏蠕动来进行的。定向算法是指在构建蠕虫时,添加新部分时擦除蠕虫紧前部分的概率最小的算法。我们引入一种简单的数值程序来最小化此概率。该程序仅取决于适当定义的局部概率,并且应具有普遍适用性。此外,我们展示了如何从蠕虫到达远离其起点的位点((r,\tau))的概率直接获得关联函数(C(r,\tau)),而与是否使用该算法的定向版本无关。针对定向和非定向几何蠕虫算法,给出了蒙特卡罗算法有效性的详细解析证明。给出了量子转子模型的自相关时间和格林函数的结果。