论文标题
有效的单环质量膨胀，并具有连接的确定性图形蒙特卡洛
Efficient One-Loop-Renormalized Vertex Expansions with Connected Determinant Diagrammatic Monte Carlo
论文作者
论文摘要
我们提出了一项技术，该技术可以根据一环的肾上飞机顶点评估扰动扩张，直到大扩张订单。具体而言，我们展示了如何在粒子孔或粒子粒子通道中计算到随机相位近似的大型校正。该算法的效率是通过使用决定因素对所有对称Feynman图拓扑的贡献的总和来实现的，并通过分析进行分析的两体长距离相互作用，以产生有效的零范围相互作用。值得注意的是，算法的指数缩放率随着扰动顺序的函数而导致近似误差的多项式缩放，并在收敛序列的计算时间内进行了计算时间。为了评估我们的方法的性能，我们将其应用于平方晶格费米子哈伯德模型的非扰动状态，从半填充和报告中，与裸露的相互作用扩展算法相比，蒙特卡罗方差的显着改善以及所得扰动系列的融合特性的显着改善。
We present a technique that enables the evaluation of perturbative expansions based on one-loop-renormalized vertices up to large expansion orders. Specifically, we show how to compute large-order corrections to the random phase approximation in either the particle-hole or particle-particle channels. The algorithm's efficiency is achieved by the summation over contributions of all symmetrized Feynman diagram topologies using determinants, and by integrating out analytically the two-body long-range interactions in order to yield an effective zero-range interaction. Notably, the exponential scaling of the algorithm as a function of perturbation order leads to a polynomial scaling of the approximation error with computational time for a convergent series. To assess the performance of our approach, we apply it to the non-perturbative regime of the square-lattice fermionic Hubbard model away from half-filling and report, as compared to the bare interaction expansion algorithm, significant improvements of the Monte Carlo variance as well as the convergence properties of the resulting perturbative series.
