全模式方法用于一般张量重正化群方法
All-mode approach for general tensor renormalization group method
- RIKEN Center for Computational Science（理化学研究所计算科学中心）
- Institute for Theoretical Physics, Kanazawa University（金泽大学理论物理研究所）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
我们提出一种基于squeezer的全模式技术，将其推广至一般张量重正化群粗粒化方案，可消除系统性误差，并在二维和三维伊辛模型中用高阶TRG验证了该方法。
AI中文摘要：
我们将随机全模式技术应用于张量重正化群（TRG）方法的一般粗粒化方案。该技术具有一个显著特性，即完全避免了在粗粒化步骤中可能出现的系统性误差，同时它因随机噪声而具有统计误差。我们推广的关键要素是采用一种称为squeezer的方法，当构建好squeezer后，全模式技术即可使用。由于许多TRG方法都可以用squeezer来描述，我们的方法适用于所有此类情况。在本工作中，我们通过二维和三维伊辛模型中的高阶TRG方法演示了该新方法。
英文摘要：
We apply the stochastic all-mode technique to general coarse-graining schemes of the tensor renormalization group (TRG) approach. The technique possesses a notable characteristic of being entirely free from systematic errors which can potentially arise in the coarse-graining step, while it has statistical errors caused by random noise. The key element in our generalization is employing a method called squeezer, and the all-mode technique can be used when it is constructed. Since many TRG methods can be described in terms of the squeezers, our approach can be applicable in all such cases. In this work, we demonstrate the new method with higher-order TRG in the two- and three-dimensional Ising model.
