连续时间量子Monte Carlo中的Worm改进估计
Worm Improved Estimators in Continuous-time Quantum Monte Carlo
摘要：
我们推导出一般相互作用的改进估计，并将其用于连续时间量子蒙特卡罗方法。使用蠕虫算法，我们展示了如何测量高阶的量子导致改进的高频行为在不可约的数量，如一个粒子的自能或不可约的两个粒子顶点的非密度-密度相互作用。对于用动力学平均场论的图形扩展来计算非定域电子关联以及计算非定域电子关联，两粒子顶点的渐近性的良好知识是必不可少的。我们测试我们的算法对多轨道原子极限和Falicov-Kimball模型的分析结果。
英文摘要：
We derive the improved estimators for general interactions and employ these for the continuous-time quantum Monte Carlo method. Using a worm algorithm we show how measuring higher-ordered correlators leads to an improved high-frequency behavior in irreducible quantities such as the one-particle self-energy or the irreducible two-particle vertex for non-density-density interactions. A good knowledge of the asymptotics of the two-particle vertex is essential for calculating non-local electronic correlations using diagrammatic extensions to the dynamical mean field theory as well as for calculating susceptibilities. We test our algorithm against analytic results for the multi-orbital atomic-limit and the Falicov-Kimball model.
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