Chen Guo P, Voora Vamsee K, Agee Matthew M, Balasubramani Sree Ganesh, Furche Filipp
Department of Chemistry, University of California, Irvine, California 92697-2025; email:
Annu Rev Phys Chem. 2017 May 5;68:421-445. doi: 10.1146/annurev-physchem-040215-112308. Epub 2017 Mar 16.
Random-phase approximation (RPA) methods are rapidly emerging as cost-effective validation tools for semilocal density functional computations. We present the theoretical background of RPA in an intuitive rather than formal fashion, focusing on the physical picture of screening and simple diagrammatic analysis. A new decomposition of the RPA correlation energy into plasmonic modes leads to an appealing visualization of electron correlation in terms of charge density fluctuations. Recent developments in the areas of beyond-RPA methods, RPA correlation potentials, and efficient algorithms for RPA energy and property calculations are reviewed. The ability of RPA to approximately capture static correlation in molecules is quantified by an analysis of RPA natural occupation numbers. We illustrate the use of RPA methods in applications to small-gap systems such as open-shell d- and f-element compounds, radicals, and weakly bound complexes, where semilocal density functional results exhibit strong functional dependence.
随机相位近似（RPA）方法正迅速成为用于半局域密度泛函计算的经济高效的验证工具。我们以直观而非形式化的方式介绍RPA的理论背景，重点关注屏蔽的物理图像和简单的图形分析。将RPA相关能新分解为等离子体模式，从而以电荷密度涨落的形式对电子关联进行了吸引人的可视化。综述了超越RPA方法、RPA相关势以及RPA能量和性质计算的高效算法等领域的最新进展。通过对RPA自然占据数的分析，量化了RPA近似捕捉分子中静态关联的能力。我们举例说明了RPA方法在诸如开壳层d和f元素化合物、自由基和弱束缚配合物等小间隙系统中的应用，在这些系统中半局域密度泛函结果表现出强烈的泛函依赖性。
