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Testing density-functional approximations on a lattice and the applicability of the related Hohenberg-Kohn-like theorem

机译:在晶格上测试密度泛函近似和相关的Hohenberg-Kohn样定理的适用性

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摘要

We present a metric-space approach to quantify the performance of approximations in lattice density-functional theory for interacting many-body systems and to explore the regimes where the Hohenberg-Kohn-type theorem on fermionic lattices is applicable. This theorem demonstrates the existence of one-to-one mappings between particle densities, wave functions and external potentials. We then focus on these quantities, and quantify how far apart in metric space the approximated and exact ones are. We apply our method to the one-dimensional Hubbard model for different types of external potentials, and assess the regimes where it is applicable to one of the most used approximations in density-functional theory, the local density approximation (LDA). We find that the potential distance may have a very different behaviour from the density and wave function distances, in some cases even providing the wrong assessments of the LDA performance trends. We attribute this to the systems reaching behaviours which are borderline for the applicability of the one-to-one correspondence between density and external potential. On the contrary the wave function and density distances behave similarly and are always sensitive to system variations. Our metric-based method correctly predicts the regimes where the LDA performs fairly well and the regimes where it fails. This suggests that our method could be a practical tool for testing the efficiency of density-functional approximations.
机译:我们提出了一种度量空间方法,以量化晶格密度泛函理论中逼近多体系统的近似性能,并探索适用于费米子晶格上的Hohenberg-Kohn型定理的制度。该定理证明了粒子密度,波函数和外部电势之间存在一对一的映射关系。然后,我们关注这些量,并量化近似值和精确值在度量空间中的距离。我们将我们的方法应用于一维Hubbard模型以用于不同类型的外部电势,并评估其适用于密度泛函理论中最常用的近似之一,局部密度近似(LDA)的体制。我们发现,潜在距离可能与密度和波函数距离有很大不同,甚至在某些情况下甚至对LDA性能趋势提供了错误的评估。我们将其归因于达到行为的系统,这些行为对于密度与外部电势一一对应的适用性至关重要。相反,波函数和密度距离的行为类似,并且始终对系统变化敏感。我们基于度量的方法可以正确预测LDA表现良好的状态和失败的状态。这表明我们的方法可能是测试密度泛函近似效率的实用工具。

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