DFTpy：一个高效的面向对象的无轨道DFT模拟平台
DFTpy: An efficient and object-oriented platform for orbital-free DFT simulations
摘要：
硅材料设计受到Kohn-Sham DFT计算复杂性的阻碍，该DFT与系统尺寸成立方比例。由于新一代动能密度泛函（KEDFs）的发展，轨道自由密度泛函（OFDFT，一种线性标度方法）现在可以成功地应用于一大类半导体以及量子点和金属团簇等有限体系。在这项工作中，我们介绍了DFTpy，这是一个完全用Python 3编写的实现OFDFT的开源软件，并将计算成本高昂的操作外包给第三方模块，如NumPy和SciPy。当需要快速仿真时，DFTpy利用PyFFTW中的快速傅立叶变换（FFT）。新一代的，非局部的和密度相关的核KEDF的计算效率，采用线性样条和其他方法快速内核构建。我们通过求解在单个CPU上计算的铝金属的百万原子系统的电子结构来展示DFTpy。Python 3的实现是面向对象的，为轻松实现新功能打开了大门。作为一个例子，我们提出了一个依赖于时间的OFDFT实现（流体动力学DFT），我们用它来计算小金属簇的光谱定性恢复依赖于时间的Kohn-Sham DFT结果。Python代码库允许轻松实现API。我们展示了DFTpy和ASE的结合液态金属的分子动力学模拟（NVT）。DFTpy在MIT许可下发布。
英文摘要：
In silico materials design is hampered by the computational complexity of Kohn-Sham DFT, which scales cubically with the system size. Owing to the development of new-generation kinetic energy density functionals (KEDFs), orbital-free DFT (OFDFT, a linear-scaling method) can now be successfully applied to a large class of semiconductors and such finite systems as quantum dots and metal clusters. In this work, we present DFTpy, an open source software implementing OFDFT written entirely in Python 3 and outsourcing the computationally expensive operations to third-party modules, such as NumPy and SciPy. When fast simulations are in order, DFTpy exploits the fast Fourier transforms (FFTs) from PyFFTW. New-generation, nonlocal and density-dependent-kernel KEDFs are made computationally efficient by employing linear splines and other methods for fast kernel builds. We showcase DFTpy by solving for the electronic structure of a million-atom system of aluminum metal which was computed on a single CPU. The Python 3 implementation is object-oriented, opening the door to easy implementation of new features. As an example, we present a time-dependent OFDFT implementation (hydrodynamic DFT) which we use to compute the spectra of small metal cluster recovering qualitatively the time-dependent Kohn-Sham DFT result. The Python code base allows for easy implementation of APIs. We showcase the combination of DFTpy and ASE for molecular dynamics simulations (NVT) of liquid metals. DFTpy is released under the MIT license.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
