通过在量子化学程序包之间交换基于网格的数据,实现可互操作的工作流程

Kevin Focke, Matteo De Santis, Mario Wolter, Jessica A. Martinez B, Valérie Vallet, André Severo Pereira Gomes, Małgorzata Olejniczak, Christoph R. Jacob
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引用次数: 0

摘要

量子化学子系统和嵌入方法需要复杂的工作流程,可能涉及多个量子化学程序包。此外,这种工作流程需要交换大量数据,而这些数据超出了分子结构和能量等简单量的范围。在此,我们介绍了通过交换电子密度和嵌入电势作为网格数据来应对这一互操作性挑战的方法。我们介绍了为此在专用代码 PyEmbed 中实施的方法,该代码目前是 Python 脚本框架的一部分。我们讨论了 PyEmbed 如何促进量子化学子系统和嵌入方法的发展,并重点介绍了 PyEmbed 支持的几种应用,包括密度函数理论(DFT)嵌入方案中的波函数理论(WFT),混合非相对论和相对论电子结构方法,实时时变 DFT-in-DFT 方法,基于密度的多体扩展,以及包括实空间数据分析和可视化在内的工作流程。我们的方法特别展示了交换基于网格的(复杂)数据的优点,以及量子化学模块化软件开发的潜力,而这取决于促进互操作性的库。
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Interoperable workflows by exchanging grid-based data between quantum-chemical program packages
Quantum-chemical subsystem and embedding methods require complex workflows that may involve multiple quantum-chemical program packages. Moreover, such workflows require the exchange of voluminous data that go beyond simple quantities, such as molecular structures and energies. Here, we describe our approach for addressing this interoperability challenge by exchanging electron densities and embedding potentials as grid-based data. We describe the approach that we have implemented to this end in a dedicated code, PyEmbed, currently part of a Python scripting framework. We discuss how it has facilitated the development of quantum-chemical subsystem and embedding methods and highlight several applications that have been enabled by PyEmbed, including wave-function theory (WFT) in density-functional theory (DFT) embedding schemes mixing non-relativistic and relativistic electronic structure methods, real-time time-dependent DFT-in-DFT approaches, the density-based many-body expansion, and workflows including real-space data analysis and visualization. Our approach demonstrates, in particular, the merits of exchanging (complex) grid-based data and, in general, the potential of modular software development in quantum chemistry, which hinges upon libraries that facilitate interoperability.
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