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Pade approximant approach for obtaining finite-temperature spectral functions of quantum impurity models using the numerical renormalization group technique

机译:使用数值重归一化群技术获得量子杂质模型的有限温度谱函数的Pade近似方法

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摘要

We introduce an alternative approach for obtaining smooth finite-temperature spectral functions of quantum impurity models using the numerical renormalization group (NRG) technique. It is based on calculating first the Green's function on the imaginary-frequency axis, followed by an analytic continuation to the real-frequency axis using Pade approximants. The arbitrariness in choosing a suitable kernel in the conventional broadening approach is thereby removed and, furthermore, we find that the Pade method is able to resolve fine details in spectral functions with less artifacts on the scale of ω ~ T . We discuss the convergence properties with respect to the NRG calculation parameters (discretization A, z-averaging, truncation cutoff) and the number of Matsubara points taken into account in the analytic continuation. We test the technique on the single-impurity Anderson model and the Hubbard model (within the dynamical mean-field theory). For the Anderson impurity model, we discuss the shape of the Kondo resonance and its temperature dependence. For the Hubbard model, we discuss the inner structure of the Hubbard bands in metallic and insulating solutions at half-filling, as well as in the doped Mott insulator. Based on these test cases, we conclude that the Pade approximant approach provides improved results for spectral functions at low-frequency scales of ω (≤) T and that it is capable of resolving sharp spectral features also at high frequencies.
机译:我们介绍了一种使用数值重归一化组(NRG)技术获得量子杂质模型的光滑有限温度谱函数的替代方法。它基于首先计算虚频轴上的格林函数,然后使用Pade近似值对实频轴进行解析延拓。从而消除了在传统的扩展方法中选择合适的内核的任意性,此外,我们发现Pade方法能够解决频谱函数中的精细细节,并且在ω〜T尺度上具有较少的伪像。我们讨论了关于NRG计算参数(离散化A,z平均,截断截止)和在分析延续中考虑的松原点数的收敛性。我们在单杂质安德森模型和哈伯德模型(在动态平均场理论内)上测试了该技术。对于安德森杂质模型,我们讨论了近藤共振的形状及其温度依赖性。对于哈伯德模型,我们讨论了半填充金属和绝缘溶液以及掺杂的莫特绝缘子中哈伯德带的内部结构。基于这些测试案例,我们得出结论,帕德近似方法为ω(≤)T的低频尺度的频谱函数提供了改进的结果,并且能够在高频下解析清晰的频谱特征。

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