论文标题
通过张量网络影响功能的安德森杂质模型的实时演变
Real time evolution of Anderson impurity models via tensor network influence functionals
论文作者
论文摘要
在这项工作中，我们介绍并分析了两种基于网络的影响功能方法，以模拟量子杂质模型（例如安德森模型）的实时动力学。通过与最近的数值精确模拟的比较，我们表明这种方法准确地捕获了长期非平衡淬灭动力学。在这些张量网络中必须控制的两个参数影响功能方法是时间离散化（trotter）误差和键尺寸（张量网络截断）误差。我们表明，实际的数值不确定性是由这两个近似值的复杂相互作用控制的，这些近似值是在不同的方向上证明的。我们的工作打开了使用这些张量网络影响功能方法作为一般杂质求解器的大门。
In this work we present and analyze two tensor network-based influence functional approaches for simulating the real-time dynamics of quantum impurity models such as the Anderson model. Via comparison with recent numerically exact simulations, we show that such methods accurately capture the long-time non-equilibrium quench dynamics. The two parameters that must be controlled in these tensor network influence functional approaches are a time discretization (Trotter) error and a bond dimension (tensor network truncation) error. We show that the actual numerical uncertainties are controlled by an intricate interplay of these two approximations which we demonstrate in different regimes. Our work opens the door to using these tensor network influence functional methods as general impurity solvers.
